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       "                               Domain  \\\n",
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       "3   Physical Sciences and Geosciences   \n",
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       "..                                ...   \n",
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       "78                            General   \n",
       "79                            General   \n",
       "80                            General   \n",
       "81                            General   \n",
       "\n",
       "                                              Journal  \\\n",
       "0                          AAS: The Astronomy Journal   \n",
       "1                      AAS: The Astrophysical Journal   \n",
       "2   AAS: The Astrophysical Journal Supplement Seri...   \n",
       "3                             Astronomy and Computing   \n",
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       "..                                                ...   \n",
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       "4   http://www.global-sci.com/guide/guide.html?jou...        None          1   \n",
       "..                                                ...         ...        ...   \n",
       "77  https://joss.readthedocs.io/en/latest/submitti...    Explicit          1   \n",
       "78  https://onlinelibrary.wiley.com/page/journal/1...    Explicit          1   \n",
       "79       https://riojournal.com/about#WhatCanIPublish    Implicit          1   \n",
       "80  https://www.siam.org/publications/journals/sia...    Implicit          1   \n",
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     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "reqs_raw = pd.read_csv(\"data/SoftwareSurveyData - instructions-compute.csv\")\n",
    "reqs_raw"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "db6f9908-effd-45de-bab7-931d7bfd0079",
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      "text/plain": [
       "                               Domain Description  Archiving  Persistent Link  \\\n",
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       "80                            General    Implicit          1                1   \n",
       "81                            General    Explicit          3                3   \n",
       "\n",
       "    License  Functionality  Project  Quality + Testing  Dependencies  \\\n",
       "0         3              1        1                  1             3   \n",
       "1         3              1        1                  1             3   \n",
       "2         3              1        1                  1             3   \n",
       "3         3              1        2                  1             1   \n",
       "4         1              1        1                  1             1   \n",
       "..      ...            ...      ...                ...           ...   \n",
       "77        3              1        1                  1             2   \n",
       "78        1              1        1                  1             1   \n",
       "79        1              1        1                  1             1   \n",
       "80        1              1        1                  1             1   \n",
       "81        3              1        1                  3             1   \n",
       "\n",
       "    Documentation  Application  Future Development   \n",
       "0               3            1                    1  \n",
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       "2               3            1                    1  \n",
       "3               3            1                    1  \n",
       "4               1            1                    1  \n",
       "..            ...          ...                  ...  \n",
       "77              3            3                    2  \n",
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       "79              1            1                    1  \n",
       "80              1            1                    1  \n",
       "81              3            3                    1  \n",
       "\n",
       "[82 rows x 12 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reqs = reqs_raw.drop([\"Journal\", \"Instructions for paper preparation (link)\"], axis=1)\n",
    "reqs = reqs.rename(\n",
    "    columns={\n",
    "        \"Domain \": \"Domain\",\n",
    "        \"Persistnt Link\": \"Persistent Link\",\n",
    "        \"Depedencies\": \"Dependencies\"\n",
    "    }\n",
    ")\n",
    "reqs = reqs.replace(0, 1)  # zero was incorrectly encoded, the lowest value is 1\n",
    "reqs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0f0f4b33-b06a-4e85-b948-8e0080f35561",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Archiving</th>\n",
       "      <th>Persistent Link</th>\n",
       "      <th>License</th>\n",
       "      <th>Functionality</th>\n",
       "      <th>Project</th>\n",
       "      <th>Quality + Testing</th>\n",
       "      <th>Dependencies</th>\n",
       "      <th>Documentation</th>\n",
       "      <th>Application</th>\n",
       "      <th>Future Development</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Domain</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Engineering</th>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>General</th>\n",
       "      <td>1.38</td>\n",
       "      <td>1.50</td>\n",
       "      <td>1.75</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.50</td>\n",
       "      <td>1.12</td>\n",
       "      <td>1.50</td>\n",
       "      <td>1.50</td>\n",
       "      <td>1.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Humanities and Social Sciences</th>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Image Processing</th>\n",
       "      <td>2.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>2.50</td>\n",
       "      <td>2.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Informatics, Mathematics and Statistics</th>\n",
       "      <td>1.53</td>\n",
       "      <td>1.67</td>\n",
       "      <td>1.60</td>\n",
       "      <td>1.60</td>\n",
       "      <td>1.27</td>\n",
       "      <td>1.73</td>\n",
       "      <td>1.60</td>\n",
       "      <td>1.53</td>\n",
       "      <td>1.53</td>\n",
       "      <td>1.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Life Sciences</th>\n",
       "      <td>1.50</td>\n",
       "      <td>1.67</td>\n",
       "      <td>1.77</td>\n",
       "      <td>1.47</td>\n",
       "      <td>1.27</td>\n",
       "      <td>1.47</td>\n",
       "      <td>1.33</td>\n",
       "      <td>1.33</td>\n",
       "      <td>1.43</td>\n",
       "      <td>1.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Physical Sciences and Geosciences</th>\n",
       "      <td>1.79</td>\n",
       "      <td>1.79</td>\n",
       "      <td>1.74</td>\n",
       "      <td>1.63</td>\n",
       "      <td>1.58</td>\n",
       "      <td>1.42</td>\n",
       "      <td>2.00</td>\n",
       "      <td>1.95</td>\n",
       "      <td>1.58</td>\n",
       "      <td>1.47</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         Archiving  Persistent Link  License  \\\n",
       "Domain                                                                         \n",
       "Engineering                                   1.00             1.00     1.00   \n",
       "General                                       1.38             1.50     1.75   \n",
       "Humanities and Social Sciences                1.00             1.00     1.00   \n",
       "Image Processing                              2.00             3.00     3.00   \n",
       "Informatics, Mathematics and Statistics       1.53             1.67     1.60   \n",
       "Life Sciences                                 1.50             1.67     1.77   \n",
       "Physical Sciences and Geosciences             1.79             1.79     1.74   \n",
       "\n",
       "                                         Functionality  Project  \\\n",
       "Domain                                                            \n",
       "Engineering                                       1.00     1.00   \n",
       "General                                           1.00     1.00   \n",
       "Humanities and Social Sciences                    1.00     1.00   \n",
       "Image Processing                                  2.50     2.00   \n",
       "Informatics, Mathematics and Statistics           1.60     1.27   \n",
       "Life Sciences                                     1.47     1.27   \n",
       "Physical Sciences and Geosciences                 1.63     1.58   \n",
       "\n",
       "                                         Quality + Testing  Dependencies  \\\n",
       "Domain                                                                     \n",
       "Engineering                                           1.00          1.00   \n",
       "General                                               1.50          1.12   \n",
       "Humanities and Social Sciences                        1.00          1.00   \n",
       "Image Processing                                      3.00          2.00   \n",
       "Informatics, Mathematics and Statistics               1.73          1.60   \n",
       "Life Sciences                                         1.47          1.33   \n",
       "Physical Sciences and Geosciences                     1.42          2.00   \n",
       "\n",
       "                                         Documentation  Application  \\\n",
       "Domain                                                                \n",
       "Engineering                                       1.00         1.00   \n",
       "General                                           1.50         1.50   \n",
       "Humanities and Social Sciences                    1.00         1.00   \n",
       "Image Processing                                  2.00         2.00   \n",
       "Informatics, Mathematics and Statistics           1.53         1.53   \n",
       "Life Sciences                                     1.33         1.43   \n",
       "Physical Sciences and Geosciences                 1.95         1.58   \n",
       "\n",
       "                                         Future Development   \n",
       "Domain                                                        \n",
       "Engineering                                             1.00  \n",
       "General                                                 1.12  \n",
       "Humanities and Social Sciences                          1.00  \n",
       "Image Processing                                        2.00  \n",
       "Informatics, Mathematics and Statistics                 1.27  \n",
       "Life Sciences                                           1.13  \n",
       "Physical Sciences and Geosciences                       1.47  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reqs.groupby(\"Domain\").mean().round(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d3c6a491-1ed1-4af7-941a-4c5f52dcd508",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "reqs.Domain = reqs.Domain.replace({\n",
    "    \"Engineering\": \"Eng\",\n",
    "    \"General\": \"Gen\",\n",
    "    \"Humanities and Social Sciences\": \"Hum\",\n",
    "    \"Image Processing\": \"Image\",\n",
    "    \"Informatics, Mathematics and Statistics\": \"IMS\",\n",
    "    \"Life Sciences\": \"Life\",\n",
    "    \"Physical Sciences and Geosciences\": \"Phys\",\n",
    "})\n",
    "\n",
    "reqs = reqs.sort_values(by=\"Description\")\n",
    "\n",
    "sns.displot(reqs, x=\"Domain\", y=\"Description\", cbar=True)\n",
    "plt.xticks(rotation=45)\n",
    "plt.savefig(\"plots/req-dist.png\", bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9f75d6f8-c53c-442f-a52a-d5212da948bd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Domain</th>\n",
       "      <th>Journal</th>\n",
       "      <th>Link to exploitation results / search</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2019</th>\n",
       "      <th>2020</th>\n",
       "      <th>2021</th>\n",
       "      <th>Notes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Physical Sciences and Geosciences</td>\n",
       "      <td>AAS: The Astronomy Journal</td>\n",
       "      <td>https://iopscience.iop.org/journal/1538-3881</td>\n",
       "      <td>30</td>\n",
       "      <td>34</td>\n",
       "      <td>24</td>\n",
       "      <td>51</td>\n",
       "      <td>76</td>\n",
       "      <td>13</td>\n",
       "      <td>38</td>\n",
       "      <td>17</td>\n",
       "      <td>Summary stats over time</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Physical Sciences and Geosciences</td>\n",
       "      <td>AAS: The Astrophysical Journal</td>\n",
       "      <td>https://iopscience.iop.org/nsearch?terms=softw...</td>\n",
       "      <td>23</td>\n",
       "      <td>40</td>\n",
       "      <td>26</td>\n",
       "      <td>45</td>\n",
       "      <td>38</td>\n",
       "      <td>31</td>\n",
       "      <td>26</td>\n",
       "      <td>40</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Physical Sciences and Geosciences</td>\n",
       "      <td>AAS: The Astrophysical Journal Supplement Seri...</td>\n",
       "      <td>https://iopscience.iop.org/nsearch?terms=softw...</td>\n",
       "      <td>21</td>\n",
       "      <td>49</td>\n",
       "      <td>16</td>\n",
       "      <td>35</td>\n",
       "      <td>33</td>\n",
       "      <td>28</td>\n",
       "      <td>40</td>\n",
       "      <td>17</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Physical Sciences and Geosciences</td>\n",
       "      <td>Astronomy and Computing</td>\n",
       "      <td>https://www.sciencedirect.com/search?qs=softwa...</td>\n",
       "      <td>19</td>\n",
       "      <td>64</td>\n",
       "      <td>24</td>\n",
       "      <td>26</td>\n",
       "      <td>45</td>\n",
       "      <td>26</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Physical Sciences and Geosciences</td>\n",
       "      <td>Communications in Computational Physics</td>\n",
       "      <td>http://www.global-sci.com/intro/articles_list/...</td>\n",
       "      <td>31</td>\n",
       "      <td>33</td>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>29</td>\n",
       "      <td>31</td>\n",
       "      <td>19</td>\n",
       "      <td>13</td>\n",
       "      <td>\"Software\" search did not work</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>General</td>\n",
       "      <td>Journal of Open Research Software</td>\n",
       "      <td>https://openresearchsoftware.metajnl.com/artic...</td>\n",
       "      <td>31</td>\n",
       "      <td>15</td>\n",
       "      <td>47</td>\n",
       "      <td>33</td>\n",
       "      <td>27</td>\n",
       "      <td>33</td>\n",
       "      <td>29</td>\n",
       "      <td>35</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>General</td>\n",
       "      <td>Journal of Software: Practice and Experience</td>\n",
       "      <td>https://onlinelibrary.wiley.com/action/doSearc...</td>\n",
       "      <td>47</td>\n",
       "      <td>48</td>\n",
       "      <td>64</td>\n",
       "      <td>60</td>\n",
       "      <td>90</td>\n",
       "      <td>85</td>\n",
       "      <td>59</td>\n",
       "      <td>73</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>General</td>\n",
       "      <td>Research Ideas and Outcomes (RIO)</td>\n",
       "      <td>https://riojournal.com/browse_journal_articles...</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>17</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>General</td>\n",
       "      <td>SIAM Journal on Scientific Computing (SISC) So...</td>\n",
       "      <td>https://epubs.siam.org/action/doSearch?AfterMo...</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>29</td>\n",
       "      <td>20</td>\n",
       "      <td>34</td>\n",
       "      <td>25</td>\n",
       "      <td>20</td>\n",
       "      <td>16</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>General</td>\n",
       "      <td>SoftwareX</td>\n",
       "      <td>https://www.sciencedirect.com/search?qs=softwa...</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>39</td>\n",
       "      <td>46</td>\n",
       "      <td>75</td>\n",
       "      <td>111</td>\n",
       "      <td>164</td>\n",
       "      <td>155</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>81 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                               Domain  \\\n",
       "0   Physical Sciences and Geosciences   \n",
       "1   Physical Sciences and Geosciences   \n",
       "2   Physical Sciences and Geosciences   \n",
       "3   Physical Sciences and Geosciences   \n",
       "4   Physical Sciences and Geosciences   \n",
       "..                                ...   \n",
       "76                            General   \n",
       "77                            General   \n",
       "78                            General   \n",
       "79                            General   \n",
       "80                            General   \n",
       "\n",
       "                                              Journal  \\\n",
       "0                          AAS: The Astronomy Journal   \n",
       "1                      AAS: The Astrophysical Journal   \n",
       "2   AAS: The Astrophysical Journal Supplement Seri...   \n",
       "3                             Astronomy and Computing   \n",
       "4             Communications in Computational Physics   \n",
       "..                                                ...   \n",
       "76                  Journal of Open Research Software   \n",
       "77       Journal of Software: Practice and Experience   \n",
       "78                  Research Ideas and Outcomes (RIO)   \n",
       "79  SIAM Journal on Scientific Computing (SISC) So...   \n",
       "80                                          SoftwareX   \n",
       "\n",
       "                Link to exploitation results / search  2014  2015  2016  2017  \\\n",
       "0        https://iopscience.iop.org/journal/1538-3881    30    34    24    51   \n",
       "1   https://iopscience.iop.org/nsearch?terms=softw...    23    40    26    45   \n",
       "2   https://iopscience.iop.org/nsearch?terms=softw...    21    49    16    35   \n",
       "3   https://www.sciencedirect.com/search?qs=softwa...    19    64    24    26   \n",
       "4   http://www.global-sci.com/intro/articles_list/...    31    33    21    21   \n",
       "..                                                ...   ...   ...   ...   ...   \n",
       "76  https://openresearchsoftware.metajnl.com/artic...    31    15    47    33   \n",
       "77  https://onlinelibrary.wiley.com/action/doSearc...    47    48    64    60   \n",
       "78  https://riojournal.com/browse_journal_articles...     0     2    20    17   \n",
       "79  https://epubs.siam.org/action/doSearch?AfterMo...    28    28    29    20   \n",
       "80  https://www.sciencedirect.com/search?qs=softwa...     0    12    39    46   \n",
       "\n",
       "    2018  2019  2020  2021                           Notes  \n",
       "0     76    13    38    17         Summary stats over time  \n",
       "1     38    31    26    40                             NaN  \n",
       "2     33    28    40    17                             NaN  \n",
       "3     45    26    40    40                             NaN  \n",
       "4     29    31    19    13  \"Software\" search did not work  \n",
       "..   ...   ...   ...   ...                             ...  \n",
       "76    27    33    29    35                             NaN  \n",
       "77    90    85    59    73                             NaN  \n",
       "78     7     6     4    10                             NaN  \n",
       "79    34    25    20    16                             NaN  \n",
       "80    75   111   164   155                             NaN  \n",
       "\n",
       "[81 rows x 12 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exploitation = pd.read_csv(\"data/SoftwareSurveyData - exploitation-compute.csv\")\n",
    "exploitation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0e3c2102-b083-4d86-a971-d0410d014cbd",
   "metadata": {},
   "outputs": [
    {
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       "      <td>21</td>\n",
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       "      <td>29</td>\n",
       "      <td>35</td>\n",
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       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>General</td>\n",
       "      <td>47</td>\n",
       "      <td>48</td>\n",
       "      <td>64</td>\n",
       "      <td>60</td>\n",
       "      <td>90</td>\n",
       "      <td>85</td>\n",
       "      <td>59</td>\n",
       "      <td>73</td>\n",
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       "      <td>17</td>\n",
       "      <td>7</td>\n",
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       "      <th>79</th>\n",
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       "      <td>28</td>\n",
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       "      <td>155</td>\n",
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       "</div>"
      ],
      "text/plain": [
       "                               Domain  2014  2015  2016  2017  2018  2019  \\\n",
       "0   Physical Sciences and Geosciences    30    34    24    51    76    13   \n",
       "1   Physical Sciences and Geosciences    23    40    26    45    38    31   \n",
       "2   Physical Sciences and Geosciences    21    49    16    35    33    28   \n",
       "3   Physical Sciences and Geosciences    19    64    24    26    45    26   \n",
       "4   Physical Sciences and Geosciences    31    33    21    21    29    31   \n",
       "..                                ...   ...   ...   ...   ...   ...   ...   \n",
       "76                            General    31    15    47    33    27    33   \n",
       "77                            General    47    48    64    60    90    85   \n",
       "78                            General     0     2    20    17     7     6   \n",
       "79                            General    28    28    29    20    34    25   \n",
       "80                            General     0    12    39    46    75   111   \n",
       "\n",
       "    2020  2021  \n",
       "0     38    17  \n",
       "1     26    40  \n",
       "2     40    17  \n",
       "3     40    40  \n",
       "4     19    13  \n",
       "..   ...   ...  \n",
       "76    29    35  \n",
       "77    59    73  \n",
       "78     4    10  \n",
       "79    20    16  \n",
       "80   164   155  \n",
       "\n",
       "[81 rows x 9 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exploitation = exploitation.drop([\"Journal\", \"Link to exploitation results / search\", \"Notes\"], axis=1)\n",
    "exploitation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "dafc94ad-6dea-4ea4-ba26-c1d38ada04e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>16</td>\n",
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       "      <th>647</th>\n",
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       "      <td>155</td>\n",
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       "</table>\n",
       "<p>648 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                Domain  Year  Exploitation\n",
       "0    Physical Sciences and Geosciences  2014            30\n",
       "1    Physical Sciences and Geosciences  2014            23\n",
       "2    Physical Sciences and Geosciences  2014            21\n",
       "3    Physical Sciences and Geosciences  2014            19\n",
       "4    Physical Sciences and Geosciences  2014            31\n",
       "..                                 ...   ...           ...\n",
       "643                            General  2021            35\n",
       "644                            General  2021            73\n",
       "645                            General  2021            10\n",
       "646                            General  2021            16\n",
       "647                            General  2021           155\n",
       "\n",
       "[648 rows x 3 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exploitation = exploitation.melt(id_vars=[\"Domain\"], var_name=\"Year\", value_name=\"Exploitation\")\n",
    "exploitation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "9acccbeb-9a5d-4554-8776-d0daa943cf4c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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xbNiwNLGYmpq+MtYXnQ7Lli2jRIkSqNVqqlSp8tqPpLO0tKR9+/a0b9+er7/+Gm9vb77++mtatGiRaQwvi4mJAWDZsmVayQ6QZijuy+fxRaL1Irl7VZsv2tixYwclS5bU2vais6R169bcvn2bnTt3sm/fPpo1a8aQIUOYO3duunVm9Ty+KubsKF++PFFRUURERGhuWbOwsMDV1TXN5y4mJoZPP/2U4cOHp6nH2dlZ697LjLzqs5ed9/lV78ELb/I+6+vrc+bMmTSfnRdDYl/n31J+odOJf9avX8+9e/dISEjg7t27rF+/XusXNRMTE3744QceP37M8+fP2bx5c5p7LUuXLs3OnTuJjY3lwYMHzJ07N82HWQghhNCV5IQENkwZR1JCgq5DEW+Zvp6Kye0rA6kJ5cteLE9uXzlXEkwAc3NzXF1dcXZ2zvZ3o/79+7NhwwZ+/vlnypUrR/369bW2Ozk5MXDgQDZv3sxnn33GsmXL0q3Hw8Mjw8eDPHr0iODgYL766iuaNWuGm5ubZmKcN6FSqahUqZJmQhkPDw8CAwN5/Phxpvva29tTokQJbt68iaurq9arTJkyWY7hVcdduXJljI2NCQsLS9PGy08+sLOzo3fv3vz222989913/Pzzz+nWl1Pn0c3NTTMZ0gsvnlGfkffffx9DQ0O++eabTOuvUaMGQUFBaY7Z1dUVIyMj3NzcSE5O1orhxbFVrlxZsy6jz56HhwdHjhwhKSkp01iy+h5k5lXvs6enJykpKURGRqZp4+W8Jqv/lvILycaEEEKIXJCUEE9SfALbF35DQuxztn/3De1GjMPQxFh6NAuRVlUc+fGjGkz9K0jrMSYO1iZMbl+ZVlUcdRhd5ry9vbGysuLrr79OM1Js5MiRtG7dmgoVKvDkyRMOHjyIm5tbuvWMHz+eqlWrMnjwYAYOHIiRkREHDx7kgw8+wNbWlqJFi/Lzzz/j6OhIWFgYX3zxxWvFGRgYyOTJk+nZsyeVK1fGyMiIQ4cO8euvvzJu3DgAunXrxsyZM+nQoQOzZs3C0dGRc+fOUaJECby8vNLUOXXqVIYPH461tTWtWrUiISGB06dP8+TJE0aPHp2luF513MWKFWPMmDGMGjUKtVpNgwYNiIqKwt/fHysrK3r37s2kSZOoWbMm7u7uJCQksH379gzPcZEiRd74PELq0M369eszd+5cfHx82LNnT6ZDZZ2dnZk3bx4jRozg8ePH9OnThzJlyvD48WN+++034N8e4HHjxlG3bl2GDh1K//79NRPd7Nu3j8WLF1O+fHl8fHwYMGAAS5cuxdLSki+++IKSJUvi4+MDvPqzN3ToUL7//ns+/PBDxo8fj7W1NcePH6dOnTpUrFhRK25LS8tM34OsmDx5Ms2aNaNcuXJ8+OGHJCcns3PnTsaNG0eFChXo0aMHvXr1Yt68eXh6evLgwQMOHDiAh4cHbdu2fa1/S/lGrt8hmg/IxD9CCCFyUnJSkhJ5K1T5vk8XZW6XtprX9326KJG3QpXkpKxP4CIypouJf7IrOUWtHLvxUNl67q5y7MZDJTlFnQMRZuzlyU3Ss2LFijQTuWzZskVJ76vhxIkTFX19feXevXta64cOHaqUK1dOMTY2Vuzs7JSePXsqDx8+VBQl7cQ/iqIofn5+Sr169RRjY2PFxsZG8fb21mzft2+f4ubmphgbGyseHh6Kn5+fAihbtmxRFCXziX8ePHigDB8+XKlSpYpiYWGhWFpaKlWrVlXmzp2rpKSkaMrdunVL6dy5s2JlZaWYmZkptWrVUk6cOKEoStqJfxRFUdasWaNUr15dMTIyUooUKaK8++67yubNmzOM6cmTJwqgHDx4MEvHrVarle+++06pWLGiYmhoqNjZ2Sne3t7KoUOHFEVJnWjIzc1NMTU1VWxtbRUfHx/l5s2b6Z6D7J7H9GJevny5UqpUKcXU1FRp3769Mnfu3FdO/PNy+61bt1ZsbW0VAwMDxd7eXunQoYOye/durXInT55UWrRooVhYWCjm5uaKh4eHMmPGDM32x48fKz179lSsra0VU1NTxdvbW7l27Zpm+6s+e4qiKOfPn1datmypmQiqYcOGmkmg/vtvI7P3IL3P8rlz5xRACQ0N1az7448/NJ+VYsWKKZ06ddJsS0xMVCZNmqS4uLgohoaGiqOjo9KxY0fNZEiZHU9e8Tp/E1WK8poPXSqAoqOjsba2JioqCisrK12HI4QQogBIjIsjOTGB7QvncOfyBZzcPWg3YiyGJiYYGBqBSvXWHlRfUOX29Ts+Pp7Q0FDKlCmDiUnh7X3u168fDx48SPOMTSFE4fI6fxN1ek+mEEIIUVDdPHeKQ7/9SuuhozE2M6fdiLGYWdtgaGzC2V1/senrCTz6546uwxQiQ1FRURw9epS1a9fm6wlIhBBvnySZQgghRC64cuQgQYf/JjEujq5TvsHw/7/6JicmcvLPjYRdusCqz4dxdP1qkhJlUiCR9/j4+NCyZUsGDhyY5hEPQgjxKjLxjxBCCJEL3Bo2QVGr0TcwxMbeUfOcTAMjI7pNn8vfK34i9NxpTmzZwFV/P5p+PJCynrV1HLUQ/3r5cSVCCPE65J5M5J5MIYQQb5+iKNw4GcDfK38m5tFDDE1MGbB4OaaWch3KKrknUwgh3p7X+ZsoPZlCCCFEDrt/8wbFXcqi0sv4rhSVSkX5d+pRuponAZvWYVm0mCbB/Cf4Cg7lymt6P4UQQoj8RK5eQgghRA56GhHOb+NHYl3cnj7zfsTAyOiV5Y1MTGn00cea5Sfh/7Bx2niKlChFiwFDKVGhUm6HLIQQQuQomfhHCCGEyEFXjvoBYONQItMEMz1R9yMwNDXjYdgtnj16mMPRCSGEELlPejKFEEKIHKIoiibJdGvQOFt1uFSvSd/5P3LliB8V6tYHUofPPv7nDlUaN3/lEFwhhBAiL5AkUwghhMgh90Ou8yT8HwyMjClfxyvb9ZhZWVOzrQ8AKcnJ7F+2mId3bnP50H4+mDgDfQPDnApZCCGEyHHyc6gQQgiRQ170Ypar9Q5GpmY5UqdKpcK9UTMMjU2wLemkSTBlcnjxJlQqFVu3btUsX716lbp162JiYkL16tV1FpeLiwvfffedztoXQuQMSTKFEEKIHJKUmICevgGVGzbJsTr19PWp1b4Tfeb/SMPufQBIiH3O2gmjuX7imCSb+cGhOTDFBg59+5/lObnWZJ8+fejQoUOG28PDw2ndurVmefLkyZibmxMcHMyBAwey3e6WLVuoW7cu1tbWWFpa4u7uzsiRI7O8/6lTp/jkk0+y3b4QIm+Q4bJCCCFEDmn5yTAadu+DkYlpjtdtVcxO8/+nt28hIuQ62+bPpIxnLZp9PBDr4g453qbIAYfmwMEZqf9/8Gu4dQRCD/1/+f/rG41962E5OGh/XkJCQmjbti2lS5fOdp0HDhyga9euzJgxg/feew+VSkVQUBD79u3Lch12dnaZFxJC5HnSkymEEELkgBc9iqYWlrn+fMs6HT6gbqeu6OkbEHruNL6jB3N88waSk5JytV3xksTnr36lJKeWOzhTe78XCeYLB2dCUty/y4qSfn057OXhsiqVijNnzjBt2jRUKhVTpkwB4M6dO3Tp0gUbGxtsbW3x8fHh1q1bGdb5119/Ub9+fT7//HMqVqxIhQoV6NChAz/88EOacrVr18bExIRixYrRsWNHzbb/Dpd9+vQp/fv3x87ODisrK5o2bcr58+c126dMmUL16tVZvXo1Li4uWFtb8+GHH/Ls2TNNGbVazZw5c3B1dcXY2BhnZ2dmzJih2Z7Zcfr5+VGnTh3Mzc2xsbGhfv363L59+zXOthCFjySZQgghxBtKjI9jxahP8Vv1C0mJCbnenqGRMfW79qTXt9/j5O5BclIi/htWc3bnn7netvi/mSVe/br6V2q5Jl9mUpECK/4dtkrso/Try0Xh4eG4u7vz2WefER4ezpgxY0hKSsLb2xtLS0uOHDmCv78/FhYWtGrVisTExHTrcXBw4PLly1y6dCnDtnbs2EHHjh1p06YN586d48CBA9SpUyfD8h988AGRkZHs2rWLM2fOUKNGDZo1a8bjx481ZUJCQti6dSvbt29n+/btHDp0iNmzZ2u2jx8/ntmzZzNx4kSCgoJYu3Yt9vb2AJkeZ3JyMh06dKBRo0ZcuHCBgIAAPvnkE1Qq1eueZiEKFRkuK4QQQryhkFPHeRJ+j5DTJ2jUs99ba7doSSc+mDiDq0f9OLv7Lzy92wEQGx2FolZjblPkrcUiMtBoLJxdCVF3dR1JhhwcHDAwMMDCwkIzjPa3335DrVbzyy+/aBKqFStWYGNjg5+fHy1btkxTz7Bhwzhy5AhVq1aldOnS1K1bl5YtW9KjRw+MjY0BmDFjBh9++CFTp07V7FetWrV04zp69CgnT54kMjJSs//cuXPZunUrmzZt0ty7qVar8fX1xdLSEoCePXty4MABZsyYwbNnz1i4cCGLFy+md+/eAJQrV44GDRoAsGHDhlceZ61atYiKiqJdu3aUK1cOADc3tzc420IUDpJkCiGEEG9KTw8bB0cq1W/81ns4VCoVbg2bUKnBv237rVzGzbOnqP9hT6q1aI2env5bjalQ+PLeq7frpyZFHJrz6gTz3bHQcPS/y2ZFM6/7LTh//jw3btzQJG4vxMfHExISku4+5ubm7Nixg5CQEA4ePMjx48f57LPPWLhwIQEBAZiZmREYGMiAAQOyHENMTAxFixbVWh8XF6cVg4uLi1acjo6OREZGAnDlyhUSEhJo1qxZto6zZcuW9OnTB29vb1q0aEHz5s3p0qULjo6OWToGIQorSTKFEEKIN+RWvxGV6r1LSnKyzmJ4kWAmJcTz+N4/JMQ+57LfAaq1aJ3JniJbjMyzVu6/92T+1+FvoemEf5dVqqzXnYtiYmKoWbMma9asSbMts8l5ypUrR7ly5ejfvz8TJkygQoUKbNiwgb59+2JqmvVJsWJiYnB0dMTPzy/NNhsbG83/GxpqPzdWpVKhVqsBMm0vK8e5YsUKhg8fzu7du9mwYQNfffUV+/bto27dulk+FiEKG7knUwghhHgDKcmpk+2oVCoM/vNlVxcMjU3oPmMuzT4eRIsBQ9DT00dRFM7s2EpCbM5PICMy8d97Mss2fvX2PKJGjRpcv36d4sWL4+rqqvWytrbOcj0uLi6YmZnx/HnqZ8/DwyPLj0ipUaMGERERGBgYpImhWLFiWaqjfPnymJqaZthmVo/T09OT8ePHc+zYMapUqcLatWuz1L4QhZUkmUIIIcQb2DDlCzZOn8Cju2G6DkVDT0+f6t5tsS/rCkDQ4b/xW/ULv478lDtBF3UcXSHTaCw0mQCooMlX0OvPl5Yn5OrjS6KioggMDNR63blzJ0v79ujRg2LFiuHj48ORI0cIDQ3Fz8+P4cOHc/du+sN/p0yZwtixY/Hz8yM0NJRz587x8ccfk5SURIsWLYDU53GuW7eOyZMnc+XKFS5evMg333yTbn3NmzfHy8uLDh06sHfvXm7dusWxY8eYMGECp0+fztJxmJiYMG7cOMaOHcuqVasICQnh+PHjLF++PEvHGRoayvjx4wkICOD27dvs3buX69evy32ZQmRChssKIYQQ2fT43j+EXw9GpaeHiYVl5jvoiJVdcYo4luTZ44dY29nrOpzCp9FY7WTyv8u5xM/PD09PT611/fr145dffsl0XzMzMw4fPsy4cePo1KkTz549o2TJkjRr1gwrK6t092nUqBE//PADvXr14v79+xQpUgRPT0/27t1LxYoVAWjcuDEbN25k+vTpzJ49GysrK959991061OpVOzcuZMJEybQt29fHjx4gIODA++++65mdtismDhxIgYGBkyaNIl79+7h6OjIwIEDs3SccXFxXL16lZUrV/Lo0SMcHR0ZMmQIn376aZbbF6IwUikvHuxViEVHR2NtbU1UVFSGfziFEEKI/3p0Nwz/339DUavxGfOVrsN5peSkJCJDb1CiQmoPzMk/N5EUH0edjl0wNDLWcXTZk9vX7/j4eEJDQylTpgwmJiY5Xr8QQuQnr/M3UXoyhRBCiGwqWsqZ90Z/SX74vdbA0FCTYD57/JBjG9eQkpTEFf9DNOs7kDKetXQcoRBCiIJC7skUQgghsiEh9jnqlBSAfPdgdosiRWkzbAwWtkWJuh/B5tlT2DZ/Js8ePdR1aEIIIQoASTKFEEKIbDi6fhVLB/XmypGDug7ltalUKiq8U5++83+kZtsOqPT0uH7iGOsmfa5JnIUQQojskiRTCCGEeE0pyckEHztCbNRTTC3z7738RqZmNO7Vn56zF+JYoRJ1O3VFT18fgOiHD3QcnRBCiPxK7skUQgghXtPtC+eIexaNmbUNzlWr6zqcN2ZXugzdps7RLEfeusmaL0fh3qgZDbv3ydeJtBBCiLdPejKFEEKI1xT0/yGyleq9q+n5y+9Uenqo9FK/Fty+GIg6JYWLf+/lfsh1HUcmhBAiv5GeTCGEEOI1JMbFEnL6BABuDZvoOJrcUbt9J0qUr8TNc6dwqV4TgH+Cr2Bkaoqds4tugxNCCJHnSZIphBBCvIbI0JsAFHEsiX1ZVx1Hk3tKVqpMyUqVAUhKTGDXD/OIfhBJ7fc607Bbbx1HJ4QQIi+T4bJCCCHEayhVuQqDlv1G+9Hj892jS7IrKT4eO+cyKGo1KcnJug5H5JKIiAhatGiBubk5NjY2ug4ny3x9ffNVvFnl4uLCd999p+swXotKpWLr1q26DuO19OnThw4dOug6DC1veh6nTJlC9erVcyye7JAkUwghhHhNRiaFa9iomZU1PmMm0OmLKdT7oDsAsVFP2b5wDlGRETqOTqQnO1+cFyxYQHh4OIGBgVy7di13AntD6SVeXbt2favxuri4oFKpWL9+fZpt7u7uqFQqfH19s1xffkySM0piwsPDad269dsPKJctW7aMatWqYWFhgY2NDZ6ensyaNUuzPbuJak6cx/QS0jFjxnDgwIHXjicnyXBZIYQQIosuHNhDZOgNPJq3prhLWV2H89aV8ayl+f/Da30JPnaYkFPHqdv5Q2q174i+gaEOo8u7wmPCeZLwJM36IsZFcLRw1EFE6QsJCaFmzZqUL18+23UkJiZiZGSUg1FlztTUFFNT07fappOTEytWrODDDz/UrDt+/DgRERGYm5u/1VjyEgcHB12HkON+/fVXRo4cyaJFi2jUqBEJCQlcuHCBS5cu5Vqbb3oeLSwssLCwyKFoskd6MoUQQogsOr9vJ+f37eJe8BVdh6Jztdt3xsndg+SkRI6uX8Wqz4cRdumCrsPKc8Jjwmm3tR1dt3dN82q3tR3hMeFvJY7GjRszfPhwxo4di62tLQ4ODkyZMkWz3cXFhT/++INVq1ahUqno06cPAGFhYfj4+GBhYYGVlRVdunTh/v37mv1e9MT88ssvlClTBhMTEyC1d2Xp0qW0a9cOMzMz3NzcCAgI4MaNGzRu3Bhzc3Pq1atHSEiIpq6QkBB8fHywt7fHwsKC2rVrs3//fq1juH37NqNGjUKlUmmGq6fXE/jXX39Ru3ZtTExMKFasGB07dtRsW7JkCeXLl8fExAR7e3vef//91z6fPXr04NChQ9y5c0ez7tdff6VHjx4YGGj34cyfP5+qVatibm6Ok5MTgwcPJiYmBgA/Pz/69u1LVFSU5phefl9iY2P5+OOPsbS0xNnZmZ9//lmr7jt37tClSxdsbGywtbXFx8eHW7duaba/6GGbOXMm9vb22NjYMG3aNJKTk/n888+xtbWlVKlSrFixQqvecePGUaFCBczMzChbtiwTJ04kKSlJc76nTp3K+fPnNTG/6Ln9b6/a3bt36datG7a2tpibm1OrVi1OnEidOO38+fM0adIES0tLrKysqFmzJqdPn87wnL/qPL6Iy8bGhj179uDm5oaFhQWtWrUiPPzff2MpKSmMHj0aGxsbihYtytixY1EUJcM2AbZt20aXLl3o168frq6uuLu7061bN2bMmAGk/htYuXIlf/75p+Z8+Pn55dh5TExMZOjQoTg6OmJiYkLp0qU1vaguLi4AdOzYEZVKpVlOr4f0119/xd3dHWNjYxwdHRk6dCgAiqIwZcoUnJ2dMTY2pkSJEgwfPvyV5yQrJMkUQgghsiAhNhZ1Sgp6+vpU8Gqg63B0rmgpJz6YOIM2Qz/DzNqGx/fusnH6l1w/FZCmbEG8jzM2KZbYpFjNF9S45Dhik2JJUacAkJCSQGxSLA/iHpCYkphuHYkpidyPTU3Y1IpaU2dGbbyplStXYm5uzokTJ5gzZw7Tpk1j3759AJw6dYpWrVrRpUsXwsPDWbhwIWq1Gh8fHx4/fsyhQ4fYt28fN2/epGvXrlr13rhxgz/++IPNmzcTGBioWT99+nR69epFYGAglSpVonv37nz66aeMHz+e06dPoyiK5osuQExMDG3atOHAgQOcO3eOVq1a0b59e8LCwgDYvHkzpUqVYtq0aYSHh2slDy/bsWMHHTt2pE2bNpw7d44DBw5Qp04dAE6fPs3w4cOZNm0awcHB7N69m3ffffe1z6W9vT3e3t6sXLkSSE0GN2zYwMcff5ymrJ6eHosWLeLy5cusXLmSv//+m7FjxwJQr149vvvuO6ysrDTHNGbMGM2+8+bNo1atWpw7d47BgwczaNAggoODAUhKSsLb2xtLS0uOHDmCv7+/JrFKTPz3M/f3339z7949Dh8+zPz585k8eTLt2rWjSJEinDhxgoEDB/Lpp59y9+5dzT6Wlpb4+voSFBTEwoULWbZsGQsWLABShyd/9tlnuLu7a2L+72cCUt/PRo0a8c8//7Bt2zbOnz/P2LFjUavVQGqiXqpUKU6dOsWZM2f44osvMDTMeDTEq87jC7GxscydO5fVq1dz+PBhwsLC0pxPX19ffv31V44ePcrjx4/ZsmVLhm1Caq/i8ePHuX37drrbx4wZQ5cuXTQJbXh4OPXq1cux87ho0SK2bdvG77//TnBwMGvWrNEkk6dOnQJgxYoVhIeHa5b/68cff2TIkCF88sknXLx4kW3btuHqmjpx3R9//MGCBQtYunQp169fZ+vWrVStWvWV5yRLFKFERUUpgBIVFaXrUIQQQuRxT+9H6DqEPCcu5pmy75clyorRg5SkxETNupSUZCUhLk6JvBWqJMbH5Xi7uX39jouLU4KCgpS4uLSxV/GtolTxraI8inukKIqi+GzxUar4VlFOhp9UFEVRRh0cpVTxraLMPz1fUza91wfbPlAURVGuP76uVPGtojRc1zDDNl5H7969FR8fH81yo0aNlAYNGmiVqV27tjJu3DjNso+Pj9K7d2/N8t69exV9fX0lLCxMs+7y5csKoJw8mXqckydPVgwNDZXIyEitugHlq6++0iwHBAQogLJ8+XLNunXr1ikmJiavPA53d3fl+++/1yyXLl1aWbBggVaZFStWKNbW1pplLy8vpUePHunW98cffyhWVlZKdHT0K9t9lRcxbN26VSlXrpyiVquVlStXKp6enoqiKIq1tbWyYsWKDPffuHGjUrRo0Qzjf7mdjz76SLOsVquV4sWLKz/++KOiKIqyevVqpWLFiopardaUSUhIUExNTZU9e/YoipL6OShdurSSkpKiKVOxYkWlYcN/P2fJycmKubm5sm7dugxj/vbbb5WaNWtqlidPnqxUq1YtTTlA2bJli6IoirJ06VLF0tJSefQo/c+vpaWl4uvrm2GbmUnvPALKjRs3NOt++OEHxd7eXrPs6OiozJkzR7OclJSklCpVSuvfyn/du3dPqVu3rgIoFSpUUHr37q1s2LBB65z+999bRrJzHocNG6Y0bdpU633OqGxG9ZYoUUKZMGFCuvvPmzdPqVChgpL4/7/dr/Kqv4n/JT2ZQgghxGuwLm6v6xDyHBNzC5r3G0SPWQsw+H9PxO4lCwjYtI6k+Dg2TBlHUkKCjqMUHh4eWsuOjo5ERkZmWP7KlSs4OTnh5OSkWVe5cmVsbGy4cuXfIeOlS5fGzs7ule3Z26f+u3m5h8Te3p74+Hiio6OB1J6vMWPG4Obmho2NDRYWFly5ckXTk5lVgYGBNGvWLN1tLVq0oHTp0pQtW5aePXuyZs0aYmNj0y2bmbZt2xITE8Phw4f59ddf0+3FBNi/fz/NmjWjZMmSWFpa0rNnTx49epSldl8+hyqVCgcHB817dv78eW7cuIGlpaXmHjxbW1vi4+O1hiG7u7ujp/fvV357e3ut90FfX5+iRYtqfRY2bNhA/fr1cXBwwMLCgq+++ipb74Onpye2trbpbh89ejT9+/enefPmzJ49Wyvm9GTlPJqZmVGuXDnN8suf8aioKMLDw3nnnXc02w0MDKhV6997zdPj6OhIQEAAFy9eZMSIESQnJ9O7d29atWql6ZXNSE6cxz59+hAYGEjFihUZPnw4e/fufa39IyMjuXfvXob/Jj744APi4uIoW7YsAwYMYMuWLSTnwOgTSTKFEEKITPxzNYi1E8dw6eA+XYeSpxkaGQMQ8+QxNdr4ULVJS3Ys+paE2Ods/+4bYqOiSEqI13GUOeNE9xOc6H6CIsZFAFjXbh0nup+gRvEaAMxqOIsT3U/QzDn9L3YvfPnOlwCUtSnLie4n2N15d4ZtvKn/DkVUqVSZfknOiowmunm5vRf3T6a37kUMY8aMYcuWLcycOZMjR44QGBhI1apVtYZ+ZsWrJgGytLTk7NmzrFu3DkdHRyZNmkS1atV4+vTpa7UBqQlKz549mTx5MidOnKBHjx5pyty6dYt27drh4eHBH3/8wZkzZ/jhhx8AsnRcr3rPYmJiqFmzJoGBgVqva9eu0b1791fW8ap6AwIC6NGjB23atGH79u2cO3eOCRMm5Oj7AKn3DV6+fJm2bdvy999/U7ly5QyHrmb1PKZ3XEoODTevUqUKgwcP5rfffmPfvn3s27ePQ4cOZVg+p85jjRo1CA0NZfr06cTFxdGlS5fXuo84s/fBycmJ4OBglixZgqmpKYMHD+bdd9/V3DuaXZJkCiGEEJm4cvQg4deucvdK7s0mWJCYWlphamHJqrHDuHM5dTKgO5cv8OvIT3gaEVEg7tE0MzTDzNBMkyiZGphiZmiGvp4+AMb6xpgZmmGg9+qJ/I30U2di1VPpaerMqI23zc3NjTt37mhNbhMUFMTTp0+pXLlyjrfn7+9Pnz596NixI1WrVsXBwUFrEhsAIyMjUlJSXlmPh4fHKx/fYGBgQPPmzZkzZw4XLlzg1q1b/P3339mK+eOPP+bQoUP4+PhQpEjaHwPOnDmDWq1m3rx51K1blwoVKnDv3r3XPqb01KhRg+vXr1O8eHFcXV21XtbW1tk6HoBjx45RunRpJkyYQK1atShfvnya+xGz+j4EBgby+PHjDMtUqFCBUaNGsXfvXjp16pRmAqIXsnIeM2NtbY2jo6Nm4iGA5ORkzpw581r1AJrP//Pnz4H0z0dOnUcAKysrunbtyrJly9iwYQN//PGH5rwaGhq+sg5LS0tcXFxe+W/C1NSU9u3bs2jRIvz8/DQ9t29CkkwhhBAiE3r6BhgYG+PWoImuQ8kX9A0MsHFw5OOFP+Pknjrcz8ndg48X/oyNgwP6BoXnCWpFjItoEsn/MtI3yrFeytzQvHlzqlatSo8ePTh79iwnT56kV69eNGrUKNMhhtlRvnx5zeRB58+fp3v37ml6Wl1cXDh8+DD//PMPDx8+TLeeyZMns27dOiZPnsyVK1e4ePEi33zzDQDbt29n0aJFBAYGcvv2bVatWoVaraZixYrZitnNzY2HDx9mmBy5urqSlJTE999/z82bN1m9ejU//fRTmmOKiYnhwIEDPHz4MMvDd3v06EGxYsXw8fHhyJEjhIaG4ufnx/Dhw7Um8Xld5cuXJywsjPXr1xMSEsKiRYvS9DC6uLgQGhpKYGAgDx8+JCGd4fDdunXDwcGBDh064O/vz82bN/njjz8ICAggLi6OoUOH4ufnx+3bt/H39+fUqVO4ubmlG1NWzmNWjBgxgtmzZ7N161auXr3K4MGDM+3FHjRoENOnT8ff35/bt29z/PhxevXqhZ2dHV5eXprzceHCBYKDg3n48CFJSUk5dh7nz5/PunXruHr1KteuXWPjxo04ODhoZlR+kUBGRETw5EnaRyVBaq/xvHnzWLRoEdevX+fs2bN8//33QOost8uXL+fSpUvcvHmT3377DVNTU0qXLv2aZ1ebJJlCCCFEJpr2/ZTBP6/BqUoOzLhXSBgam2BmZU27EeMwNjOn3chxmFlZY2hsouvQ3ipHC0e2d9jOhnYb0ry2d9iep56T+V8qlYo///yTIkWK8O6779K8eXPKli3Lhg0bcqW9+fPnU6RIEerVq0f79u3x9vamRo0aWmWmTZvGrVu3KFeuXLr3gULqo042btzItm3bqF69Ok2bNuXkyZMA2NjYsHnzZpo2bYqbmxs//fQT69atw93dHUj9wv26PcdFixbNcEhitWrVmD9/Pt988w1VqlRhzZo1msdPvFCvXj0GDhxI165dsbOzY86cOVlq18zMjMOHD+Ps7EynTp1wc3OjX79+xMfHY2Vl9VrH8LL33nuPUaNGMXToUKpXr86xY8eYOHGiVpnOnTvTqlUrmjRpgp2dHevWrUtTj5GREXv37qV48eK0adOGqlWrMnv2bPT19dHX1+fRo0f06tWLChUq0KVLF1q3bs3UqVPTjSkr5zErPvvsM3r27Env3r3x8vLC0tJS6/E26WnevDnHjx/ngw8+oEKFCnTu3BkTExMOHDhA0aJFARgwYAAVK1akVq1a2NnZ4e/vn2Pn0dLSkjlz5lCrVi1q167NrVu32Llzp+Y+23nz5rFv3z6cnJzw9PRM9xh69+7Nd999x5IlS3B3d6ddu3Zcv34dSP03sWzZMurXr4+Hhwf79+/nr7/+0hxbdqmUnBqonI9FR0djbW1NVFTUG/2jFEIIUfAoajUqPflNNruSEuJ5GhGBjYNDjieYuX39jo+PJzQ0VOv5j6Jgmzx5MocOHdI851AI8a/X+ZsoV00hhBAiAwmxz1k6uA97f/6epESZHTU7DI1NsC1ZqtD1YIr8adeuXVnuSRRCZKzw3BQhhBBCvKbrJ47x/Mlj7gVfwcAw/fvqROYK0z2YIn97MaxWCPFmpCdTCCGEyMCVowcBcGvQWGczfAohhBD5jSSZQgghRDqePX5I2OXUKdwr1W+k42iEEEKI/EOSTCGEECIdV/0Pg6JQslJlrIvb6zocIYQQIt+QJFMIIYRIR8jp1Ad2y7MxhRBCiNcjd+ILIYQQ6Xh/wnRunjuFk7uHrkMRQggh8hVJMoUQQoh0GBgZUeGd+roOQwghhMh3ZLisEEII8RJFreag78/cunAOtTpF1+EIIYQQ+Y4kmUIIIcRL7l69zNld2/hr/izUyZJkCiHenK+vLzY2NroOQ4i3RpJMIYQQ4iX/XA0CoELdBhgYGek4GlGQJN27R9zlyyTdu5frbfXp04cOHTrkeju5pXHj1GfTqlQqTExMqFy5MkuWLNF1WNnWtWtXrl27puswhHhr5J5MIYQQ4iV1O3WlolcDVCr5HVbknKR79whp1RolMRGVkRHldu/CsEQJXYeVpw0YMIBp06YRGxvLqlWrGDJkCEWKFKFbt25pyiYmJmKUh38UMjU1xdTUVNdhCPHWyBVUCCGE+I8ijiWxcXDUdRiiAEl+8gQlMREAJTGR5CdP3mr7jRs3ZtiwYYwcOZIiRYpgb2/PsmXLeP78OX379sXS0hJXV1d27dql2SclJYV+/fpRpkwZTE1NqVixIgsXLtQ+ruRkhg8fjo2NDUWLFmXcuHH07t1bqxdVrVYza9YsTT3VqlVj06ZNmcZsZmaGg4MDZcuWZcqUKZQvX55t27Zpjmfo0KGMHDmSYsWK4e3tDcChQ4eoU6cOxsbGODo68sUXX5CcnKwVy5w5c3B1dcXY2BhnZ2dmzJih2X7nzh26dOmCjY0Ntra2+Pj4cOvWLc12Pz8/6tSpg7m5OTY2NtSvX5/bt28DcP78eZo0aYKlpSVWVlbUrFmT06dPA2mHy06ZMoXq1auzevVqXFxcsLa25sMPP+TZs2eaMs+ePaNHjx6Ym5vj6OjIggULaNy4MSNHjsz03Amha5JkCiGEEP93eK0vp/7aTGx0lK5DEXmcOjY23ZeSknofr6JWo46NJSEkhNgzZ0i8eVNr/4QrV4g9c4aEkJDUfePi/q07MfHfOv+fmOaElStXUqxYMU6ePMmwYcMYNGgQH3zwAfXq1ePs2bO0bNmSnj17EhsbmxqHWk2pUqXYuHEjQUFBTJo0iS+//JLff/9dU+c333zDmjVrWLFiBf7+/kRHR7N161atdmfNmsWqVav46aefuHz5MqNGjeKjjz7i0KFDrxW/qakpiS+dj5UrV2JkZIS/vz8//fQT//zzD23atKF27dqcP3+eH3/8keXLl/P1119r9hk/fjyzZ89m4sSJBAUFsXbtWuzt7QFISkrC29sbS0tLjhw5gr+/PxYWFrRq1YrExESSk5Pp0KEDjRo14sKFCwQEBPDJJ5+gUqkA6NGjB6VKleLUqVOcOXOGL774AkNDwwyPJyQkhK1bt7J9+3a2b9/OoUOHmD17tmb76NGj8ff3Z9u2bezbt48jR45w9uzZ1zpnQuiMkkfMmjVLAZQRI0Zo1sXFxSmDBw9WbG1tFXNzc6VTp05KRESE1n63b99W2rRpo5iamip2dnbKmDFjlKSkpNdqOyoqSgGUqKionDgUIYQQ+VDcs2fKgu4+ytwubZXIWzd1HY7Igty+fsfFxSlBQUFKXFxcmm1BFSul+4o5fkJRFEVJCA1Nu92tcob73WjbVlN3+IwZmvXhM2ZkK/bevXsrPj4+muVGjRopDRo00CwnJycr5ubmSs+ePf9tNzxcAZSAgIAM6x0yZIjSuXNnzbK9vb3y7bffatXr7OysaTs+Pl4xMzNTjh07plVPv379lG7dumXYTqNGjTTfCZOTk5XVq1crgLJ48WLNdk9PT619vvzyS6VixYqKWq3WrPvhhx8UCwsLJSUlRYmOjlaMjY2VZcuWpdvm6tWr0+yfkJCgmJqaKnv27FEePXqkAIqfn1+6+1taWiq+vr7pbluxYoVibW2tWZ48ebJiZmamREdHa9Z9/vnnyjvvvKMoiqJER0crhoaGysaNGzXbnz59qpiZmWl9VxbibXrV38T/yhP3ZJ46dYqlS5fi4aH9wOtRo0axY8cONm7ciLW1NUOHDqVTp074+/sDqcM42rZti4ODA8eOHSM8PJxevXphaGjIzJkzdXEoQggh8qmHd29jaGxCkRLFsCtdRtfhiIJIrdZp8y9/z9LX16do0aJUrVpVs+5Fj15kZKRm3Q8//MCvv/5KWFgYcXFxJCYmUr16dQCioqK4f/8+derU0aq3Zs2aqP9/rDdu3CA2NpYWLVpoxZKYmIinp+cr412yZAm//PILiYmJ6OvrM2rUKAYNGqTZXrNmTa3yV65cwcvLS9OzCFC/fn1iYmK4e/cuERERJCQk0KxZs3TbO3/+PDdu3MDS0lJrfXx8PCEhIbRs2ZI+ffrg7e1NixYtaN68OV26dMHRMXVo/ejRo+nfvz+rV6+mefPmfPDBB5QrVy7D43NxcdFqy9HRUXPub968SVJSkta5tba2pmLFiq88Z0LkFTpPMmNiYujRowfLli3TGs4QFRXF8uXLWbt2LU2bNgVgxYoVuLm5cfz4cerWrcvevXsJCgpi//792NvbU716daZPn864ceOYMmVKnr4BXAghRN5SqpI7ny5dzbNHD3QdisgHKp49k+56lbExAIbOzpTdsZ3Qjp0092Kip5eaaL74L6AyMqLMls1akwAVHzOG4i/uuzPIua9q/x26qVKptNa9SM5eJIjr169nzJgxzJs3Dy8vLywtLfn22285ceJEltuMiYkBYMeOHZQsWVJrm/H/z1VGevTowYQJEzA1NcXR0RE9Pe27vMzNzbMcB5DpxDsxMTHUrFmTNWvWpNlmZ2cHpH4XHT58OLt372bDhg189dVX7Nu3j7p16zJlyhS6d+/Ojh072LVrF5MnT2b9+vV07Ngx3fbSez/UOv4hQoicovN7MocMGULbtm1p3ry51vozZ86QlJSktb5SpUo4OzsTEBAAQEBAAFWrVtX88gbg7e1NdHQ0ly9fzrDNhIQEoqOjtV5CCCGEgaEhRRxkxk+ROT0zs3RfKn19AFR6ehiXK0e53btw+WMTJb6d829PplpNiW/n4PLHJsrt3oVxuXLovZQA6RkZ/VunDn8w9/f3p169egwePBhPT09cXV0JCQnRbLe2tsbe3p5Tp05p1qWkpGjdN1i5cmWMjY0JCwvD1dVV6+Xk5PTK9q2trXF1daVkyZJpEsz0uLm5ERAQgKIoWsdgaWlJqVKlKF++PKamphw4cCDd/WvUqMH169cpXrx4mlitra015Tw9PRk/fjzHjh2jSpUqrF27VrOtQoUKjBo1ir1799KpUydWrFiRadzpKVu2LIaGhlrnNioqSh6DIvINnSaZ69ev5+zZs8yaNSvNtoiICIyMjNI8uNbe3p6IiAhNmZcTzBfbX2zLyKxZs7C2tta8MvsjJ4QQomA7u2sbOxfPI/x6sK5DEQWMYYkSmLq7Y1S2rNZ6o7JlMXV3z9OPMSlfvjynT59mz549XLt2jYkTJ2olPQDDhg1j1qxZ/PnnnwQHBzNixAiePHmi6RW1tLRkzJgxjBo1ipUrVxISEsLZs2f5/vvvWblyZY7GO3jwYO7cucOwYcO4evUqf/75J5MnT2b06NHo6elhYmLCuHHjGDt2LKtWrSIkJITjx4+zfPlyILXntFixYvj4+HDkyBFCQ0Px8/Nj+PDh3L17l9DQUMaPH09AQAC3b99m7969XL9+HTc3N+Li4hg6dCh+fn7cvn0bf39/Tp06hZubW7aOxdLSkt69e/P5559z8OBBLl++TL9+/dDT09MaDixEXqWz4bJ37txhxIgR7Nu3DxMTk7fa9vjx4xk9erRmOTo6WhJNIYQopBRF4cL+3Ty6G4ZT5ao4lpd7nkTOMyhSBJWRkeY5mQZFiug6pEx9+umnnDt3jq5du6JSqejWrRuDBw/WeszJuHHjiIiIoFevXujr6/PJJ5/g7e2N/v97dAGmT5+OnZ0ds2bN4ubNm9jY2FCjRg2+/PLLHI23ZMmS7Ny5k88//5xq1apha2tLv379+OqrrzRlJk6ciIGBAZMmTeLevXs4OjoycOBAIPWRKYcPH2bcuHF06tSJZ8+eUbJkSZo1a4aVlRVxcXFcvXqVlStX8ujRIxwdHRkyZAiffvopycnJPHr0iF69enH//n2KFStGp06dmDp1araPZ/78+QwcOJB27dphZWXF2LFjuXPnzlv/3ixEdqiUl8cUvEVbt26lY8eOWn+EUlJSUKlU6OnpsWfPHpo3b86TJ0+0ejNLly7NyJEjGTVqFJMmTWLbtm0EBgZqtoeGhlK2bFnOnj2b6Q3lL0RHR2NtbU1UVBRWVlY5dYhCCCHygchbN1k9bjj6BgYM/Pk3TMwtdB2SyKLcvn7Hx8cTGhpKmTJlcuSLfdK9eyQ/eYJBkSJ5ugfzTajVatzc3OjSpQvTp0/XdTgFyvPnzylZsiTz5s2jX79+ug5HFEKv8zdRZz2ZzZo14+LFi1rr+vbtS6VKlRg3bhxOTk4YGhpy4MABOnfuDEBwcDBhYWF4eXkB4OXlxYwZM4iMjKR48eIA7Nu3DysrKypXrvx2D0gIIUS+dOWoHwBla9aRBFPkKsMSJQpccvli2GijRo1ISEhg8eLFhIaG0r17d12Hlu+dO3eOq1evUqdOHaKiopg2bRoAPj4+Oo5MiMzpLMm0tLSkSpUqWuvMzc0pWrSoZn2/fv0YPXo0tra2WFlZMWzYMLy8vKhbty4ALVu2pHLlyvTs2ZM5c+YQERHBV199xZAhQzKdsUwIIYRQq1O46p/6QHi3Bo11G4wQ+ZCenh6+vr6MGTMGRVGoUqUK+/fvz/a9iELb3LlzCQ4OxsjIiJo1a3LkyBGKFSum67CEyJTOH2HyKgsWLEBPT4/OnTuTkJCAt7c3S5Ys0WzX19dn+/btDBo0CC8vL8zNzendu7fmlx4hhBDiVe4GXSbm8SOMzc0p41lb1+EIke84OTlpnl8ucpanpydnzqT/qBwh8jqd3ZOZl8g9mUIIUTilJCcTdjGQmKePqdqkpa7DEa8pv92TKYQQ+Vm+uCdTCCGE0DV9AwPKeNbSdRhCCCFEgaLT52QKIYQQuvJP8BVunD5BSnKSrkMRQgghChRJMoUQQhRKp7Zt4s9vp3N88wZdhyKEEEIUKJJkCiGEKHQS42K5df4sAJXqvavjaIQQQoiCRe7JFEIIUegYmZrx8XdLuXX+LEVLOes6HCGEEKJAkZ5MIYQQhZJVseJ4NGul6zCEEK/QuHFjRo4c+coyvr6+2NjYvJV4ctKtW7dQqVQEBgbqNA6VSsXWrVuzXH7KlClUr1491+IBcHFx4bvvvsvVNkTukiRTCCFEoRIVeZ+ATet4GhGu61BEIaNWKzyJeI5anftPj+vTpw8dOnRIs97Pzw+VSsXTp09zPYacsHnzZqZPn65ZTi/56Nq1K9euXXvLkb0doaGhdO/enRIlSmBiYkKpUqXw8fHh6tWrOdZGeHg4rVu3zrH6ALZs2ULdunWxtrbG0tISd3f3TH8seNmpU6f45JNPcjQm8XbJcFkhhBCFypWjfhzbuIa7Vy7ywcSZug5HFBJqtcL+FUFcP3Wf8rXtad63Mnp6Kl2HlefZ2tpmWsbU1BRTU9O3EM3blZSURIsWLahYsSKbN2/G0dGRu3fvsmvXrhz9kcDBwSHH6gI4cOAAXbt2ZcaMGbz33nuoVCqCgoLYt29fluuws7PL0ZjE2yc9mUIIIQqV2xfOAeDWsKmOIxGFxcsJJsD1U/fZvyLorfRoZia9oY/fffcdLi4umuUXvaIzZ87E3t4eGxsbpk2bRnJyMp9//jm2traUKlWKFStWaNUzbtw4KlSogJmZGWXLlmXixIkkJf37yKAXba9evRoXFxesra358MMPefbsmabMy8NlGzduzO3btxk1ahQqlQqVKjVJT2+47J9//kmNGjUwMTGhbNmyTJ06leTkZAAURWHKlCk4OztjbGxMiRIlGD58eIbnKCQkBB8fH+zt7bGwsKB27drs379fq4yLiwszZ87k448/xtLSEmdnZ37++WetMidPnsTT0xMTExNq1arFuXPnMmwT4PLly4SEhLBkyRLq1q1L6dKlqV+/Pl9//TV169bVlLt48SJNmzbF1NSUokWL8sknnxATE6NV16+//oq7uzvGxsY4OjoydOhQzbb/DpfN7H3LzF9//UX9+vX5/PPPqVixIhUqVKBDhw788MMPacrVrl0bExMTihUrRseOHbXO58s91k+fPqV///7Y2dlhZWVF06ZNOX/+vGZ7Vj5LarWaOXPm4OrqirGxMc7OzsyYMUOz/c6dO3Tp0gUbGxtsbW3x8fHh1q1bmu1+fn7UqVMHc3NzbGxsqF+/Prdv387yeSlsJMkUQghRqHwwcQadx0+lfJ16ug5F5GNJCSlZeyWlaCWYL1w/dZ+9yy+TEJecaR2Kovtk9O+//+bevXscPnyY+fPnM3nyZNq1a0eRIkU4ceIEAwcO5NNPP+Xu3buafSwtLfH19SUoKIiFCxeybNkyFixYoFVvSEgIW7duZfv27Wzfvp1Dhw4xe/bsdGPYvHkzpUqVYtq0aYSHhxMenv6Q9yNHjtCrVy9GjBhBUFAQS5cuxdfXV5NQ/PHHHyxYsIClS5dy/fp1tm7dStWqVTM89piYGNq0acOBAwc4d+4crVq1on379oSFhWmVmzdvniZ5HDx4MIMGDSI4OFhTR7t27ahcuTJnzpxhypQpjBkz5pXn3M7ODj09PTZt2kRKSkq6ZZ4/f463tzdFihTh1KlTbNy4kf3792slkT/++CNDhgzhk08+4eLFi2zbtg1XV9cM283K+/YqDg4OXL58mUuXLmVYZseOHXTs2JE2bdpw7tw5Dhw4QJ06dTIs/8EHHxAZGcmuXbs4c+YMNWrUoFmzZjx+/FhTJrPP0vjx45k9ezYTJ04kKCiItWvXYm9vD6T2Gnt7e2NpacmRI0fw9/fHwsKCVq1akZiYSHJyMh06dKBRo0ZcuHCBgIAAPvnkE80PHSItGS4rhBCiUNHT18elek1dhyHyuZ9HHMpSOTtnSx6EPUt3W8iZSELORGZax8ffNsDU0ui14gPYvn07FhYWWusySlYyY2try6JFi9DT06NixYrMmTOH2NhYvvzyS+DfL/BHjx7lww8/BOCrr77S7O/i4sKYMWNYv349Y8eO1axXq9X4+vpiaWkJQM+ePTlw4IBWD9PLMejr62NpafnKIZ5Tp07liy++oHfv3gCULVuW6dOnM3bsWCZPnkxYWBgODg40b94cQ0NDnJ2dX5ngVKtWjWrVqmmWp0+fzpYtW9i2bZtWMtemTRsGDx4MpPYGLliwgIMHD1KxYkXWrl2LWq1m+fLlmJiY4O7uzt27dxk0aFCG7ZYsWZJFixYxduxYpk6dSq1atWjSpAk9evSgbNmyAKxdu5b4+HhWrVqFubk5AIsXL6Z9+/Z888032Nvb8/XXX/PZZ58xYsQITd21a9fOsN2svG+vMmzYMI4cOULVqlUpXbo0devWpWXLlvTo0QNjY2MAZsyYwYcffsjUqVO1znN6jh49ysmTJ4mMjNTsP3fuXLZu3cqmTZs0926+6rP07NkzFi5cyOLFizWfi3LlytGgQQMANmzYgFqt5pdfftEkjitWrMDGxgY/Pz9q1apFVFQU7dq1o1y5cgC4ubll6XwUVtKTKYQQolBQq1PY/eN3XD95DHU2v2gL8boySjDfhiZNmhAYGKj1+uWXX7JVl7u7O3p6/35ttLe31+r909fXp2jRokRG/ps0b9iwgfr16+Pg4ICFhQVfffVVmt4/FxcXTVIA4OjoqFVHdpw/f55p06ZhYWGheQ0YMIDw8HBiY2P54IMPiIuLo2zZsgwYMIAtW7ZohtKmJyYmhjFjxuDm5oaNjQ0WFhZcuXIlzbF4eHho/l+lUuHg4KA5litXruDh4YGJiYmmjJeXV6bHMmTIECIiIlizZg1eXl5s3LgRd3d3zf2NV65coVq1apoEE6B+/fqo1WqCg4OJjIzk3r17NGvWLGsnj6y9b69ibm7Ojh07uHHjBl999RUWFhZ89tln1KlTh9jYWAACAwOzHNP58+eJiYmhaNGiWu9paGgoISEhmnKv+ixduXKFhISEDNs8f/48N27cwNLSUlO/ra0t8fHxhISEYGtrS58+ffD29qZ9+/YsXLgww550kUp6MoUQQhQKYZcucNlvPyFnTjLwp9qAvq5DEvnYJwsbZVpGrVbwW3OVG6czTprK1SxOk48qvXISIAOj7PUJmJubpxkW+fJwVgA9Pb00w3HTu//O0NBQa1mlUqW7Tq1WAxAQEECPHj2YOnUq3t7eWFtbs379eubNm5dpvS/qyK6YmBimTp1Kp06d0mwzMTHBycmJ4OBg9u/fz759+xg8eDDffvsthw4dShMPwJgxY9i3bx9z587F1dUVU1NT3n//fRITE3P9WCB1+Gr79u1p3749X3/9Nd7e3nz99de0aNEi031fd0KkrL5vWVGuXDnKlStH//79mTBhAhUqVGDDhg307dv3teKKiYnB0dERPz+/NNtevhf3Vec/s/ZiYmKoWbMma9asSbPtxSREK1asYPjw4ezevZsNGzbw1VdfsW/fPq37Y8W/JMkUQghRKFw5chCAinUboG+Q9oukEK/D0DhrP1K0+NgdlUqV5p5MIE/MMmtnZ0dERASKomiGCebEcxuPHTtG6dKlmTBhgmZdTkySYmRklOmQ3xo1ahAcHPzK+w5NTU01iduQIUOoVKkSFy9epEaNGmnK+vv706dPH83ENDExMVoTwmSFm5sbq1evJj4+XtObefz48deqA1ITp0qVKnHs2DFNvb6+vjx//lzTm+nv768Z1mxpaYmLiwsHDhygSZMmmdafW++bi4sLZmZmPH/+HEjt9T1w4AB9+/bNdN8aNWoQERGBgYGB1oRUr6N8+fKYmppy4MAB+vfvn24bGzZsoHjx4lhZWWVYj6enJ56enowfPx4vLy/Wrl0rSWYGZLisEEKIAi8pIZ7rJwMAcGuY+RctIXKKnp6K5n0rU762vdb6vJBgQuqMrQ8ePGDOnDmEhITwww8/sGvXrjeut3z58oSFhbF+/XpCQkJYtGgRW7ZseeN6XVxcOHz4MP/88w8PHz5Mt8ykSZNYtWoVU6dO5fLly1y5coX169dr7jX09fVl+fLlXLp0iZs3b/Lbb79hampK6dKlMzyWzZs3ExgYyPnz5+nevftr91B2794dlUrFgAEDCAoKYufOncydO/eV+wQGBuLj48OmTZsICgrixo0bLF++nF9//RUfHx8AevTogYmJCb179+bSpUscPHiQYcOG0bNnT82kNlOmTGHevHksWrSI69evc/bsWb7//vsMj/VN37cpU6YwduxY/Pz8CA0N5dy5c3z88ceaR7IATJ48mXXr1jF58mSuXLnCxYsX+eabb9Ktr3nz5nh5edGhQwf27t3LrVu3OHbsGBMmTOD06dNZisnExIRx48YxduxYVq1aRUhICMePH2f58uWa81isWDF8fHw4cuQIoaGh+Pn5MXz4cO7evUtoaCjjx48nICCA27dvs3fvXq5fvy73Zb6CJJlCCCEKvJDTJ0iKj8O6uD0lKlTSdTiikPlvoplXEkxI7QlbsmQJP/zwA9WqVePkyZOZznqaFe+99x6jRo1i6NChVK9enWPHjjFx4sQ3rnfatGncunWLcuXKZfgsRW9vb7Zv387evXupXbs2devWZcGCBZok0sbGhmXLllG/fn08PDzYv38/f/31F0WLFk23vvnz51OkSBHq1atH+/bt8fb2TrfH81UsLCz466+/uHjxIp6enkyYMCHDpOqFUqVK4eLiwtSpU3nnnXeoUaMGCxcuZOrUqZqeRjMzM/bs2cPjx4+pXbs277//Ps2aNWPx4sWaenr37s13333HkiVLcHd3p127dly/fj3dNnPifWvUqBE3b96kV69eVKpUidatWxMREcHevXupWLEikPrjxsaNG9m2bRvVq1enadOmnDx5Mt36VCoVO3fu5N1336Vv375UqFCBDz/8kNu3b2sS6ayYOHEin332GZMmTcLNzY2uXbtq7tk0MzPj8OHDODs706lTJ9zc3OjXrx/x8fFYWVlhZmbG1atX6dy5MxUqVOCTTz5hyJAhfPrpp691bgoTlZIX5sXWsejoaKytrYmKinplF7kQQoj8acs3U7l59hR1O3Wlfteeug5H5JDcvn7Hx8cTGhpKmTJltCZsyS61WiEqMhbr4mZ5IsEUQojX8Tp/E+WeTCGEEAVe7fadMbcpIkNlhU7p6ako4mCeeUEhhMjnJMkUQghR4JWqXIVSlavoOgwhhBCiUJB7MoUQQhRotwLPkJQQr+swhBBCiEJDkkwhhBAF1tOIcP6YNZmlg3qTGB+n63CEEEKIQkGSTCGEEAXWlaN+ADi6VsTI5PUeSi6EEEKI7JF7MoUQQhRY1Vq0xsTCAhuHEroORQghhCg0JMkUQghRYJlZ2+DZqr2uwxBCCCEKFRkuK4QQokAKOXOCh3du6zoMIYQQotCRJFMIIUSBo05JYe/S71k5Zghhly7oOhwhhBCiUJEkUwghRIETdvkCsVFPMbWypmSlyroOR4gCy9fXFxsbG12HoaFSqdi6dauuwxCi0JMkUwghRIFTuko1uk6eTdM+n6BvINMPiMKnT58+qFSqNK9WrVrlaDtdu3bl2rVrOVrnmwgPD6d169a6DkOIQk+uvEIIIQoclZ4epSpX0XUYQmi5eHAve39aRMuBw6napGWut9eqVStWrFihtc7Y2DhH2zA1NcXUVPePB0pMTMTIyAgHBwddhyKEQHoyhRBCFDBhly5w5chBkuLjdR2KEBpJCfEcXbsSgKPrVpGUkPufT2NjYxwcHLReRYoU0WxXqVT88ssvdOzYETMzM8qXL8+2bdu06ti2bRvly5fHxMSEJk2asHLlSlQqFU+fPgXSDpedMmUK1atXZ/Xq1bi4uGBtbc2HH37Is2fPNGXUajWzZs2iTJkymJqaUq1aNTZt2qTV7qVLl2jdujUWFhbY29vTs2dPHj58qNneuHFjhg4dysiRIylWrBje3t6aY3oxXPbWrVuoVCo2b95MkyZNMDMzo1q1agQEBGi1tWzZMpycnDAzM6Njx47Mnz8/Tw0BFiI/kiRTCCFEgXLqrz/YuXgep/7arOtQRAGWFB+f7kutTgFAUas16+Kfx3Bo9XJin0UDEBsdxUHfZZpEMykxId26UpKTcv04pk6dSpcuXbhw4QJt2rShR48ePH78GIDQ0FDef/99OnTowPnz5/n000+ZMGFCpnWGhISwdetWtm/fzvbt2zl06BCzZ8/WbJ81axarVq3ip59+4vLly4waNYqPPvqIQ4cOAfD06VOaNm2Kp6cnp0+fZvfu3dy/f58uXbpotbNy5UqMjIzw9/fnp59+yjCeCRMmMGbMGAIDA6lQoQLdunUjOTkZAH9/fwYOHMiIESMIDAykRYsWzJgx47XPoxBCmwyXFUIIUWA8f/qE2+fPAeDWoJGOoxEF2aLe76e7vsukmTi5e/D0fji/jvwUAEMTE5ISEkBRUgspChf/3kPImeM06Nabq/6HCbsYmKaudzp2ocGHvbId4/bt27GwsNBa9+WXX/Lll19qlvv06UO3bt0AmDlzJosWLeLkyZO0atWKpUuXUrFiRb799lsAKlasyKVLlzJNwtRqNb6+vlhaWgLQs2dPDhw4wIwZM0hISGDmzJns378fLy8vAMqWLcvRo0dZunQpjRo1YvHixXh6ejJz5kxNnb/++itOTk5cu3aNChUqAFC+fHnmzJmT6XkYM2YMbdu2BVKTand3d27cuEGlSpX4/vvvad26NWPGjAGgQoUKHDt2jO3bt2darxAiY5JkCiGEKDCCA46gKGocXStSxLGkrsMRAiDDoduxUVHs/WkRzlWr50q7TZo04ccff9RaZ2trq7Xs4eGh+X9zc3OsrKyIjIwEIDg4mNq1a2uVr1OnTqbturi4aBJMAEdHR02dN27cIDY2lhYtWmjtk5iYiKenJwDnz5/n4MGDaRJkSO0lfZFk1qxZM9NYQPsYHR0dAYiMjKRSpUoEBwfTsWNHrfJ16tSRJFOINyRJphBCiALjypGDAFRq0Fi3gYgCb/jKTemu1zcyBMDG3pHhKzdx+fABjm1cS9yz6H97MgFUKsysrGnQrReV6jcCtZKmLj0D/TeK0dzcHFdX11eWMTQ01FpWqVSo1eo3avdVdcbExACwY8cOSpbU/iHoxaREMTExtG/fnm+++SZN3S+SREg9vteNR6VSAbzxMQohXk2STCGEEAXC43v/EBFyHZWeHpXqNdR1OKKAMzQxeeV2lZ4ehiYmVG/ZFvdGzTi0ejnn9+9OTTRVKqo1b0Wjnv0wNH51PbpUsWJFdu7cqbXu1KlTb1Rn5cqVMTY2JiwsjEaN0h/SXqNGDf744w9cXFwwyOVHEFWsWDHNMb3pMQohZOIfIYQQBYSBoSGerdpTuWETzKxtdB2OEBqGxiY06tkPMysrAMysrN9KgpmQkEBERITW6+UZWjPz6aefcvXqVcaNG8e1a9f4/fff8fX1Bf7tEXxdlpaWjBkzhlGjRrFy5UpCQkI4e/Ys33//PStXps6+O2TIEB4/fky3bt04deoUISEh7Nmzh759+5KSkpKtdjMybNgwdu7cyfz587l+/TpLly5l165d2T4+IUQqSTKFEEIUCFZ2xWna91NaDR6l61CESMPQ2IQG3XoD0KBbr7fSg7l7924cHR21Xg0aNMjy/mXKlGHTpk1s3rwZDw8PfvzxR83ssm/yvM3p06czceJEZs2ahZubG61atWLHjh2UKVMGgBIlSuDv709KSgotW7akatWqjBw5EhsbG/T0cvara/369fnpp5+YP38+1apVY/fu3YwaNQqTTHqqhRCvplIUJe1NAIVMdHQ01tbWREVFYfX/XxmFEELkH8+fPsHAyAhjs6zdoyUKhty+fsfHxxMaGkqZMmUk6fi/GTNm8NNPP3Hnzh1dh5JrBgwYwNWrVzly5IiuQxEiT3mdv4lyT6YQQoh87/jm9Vz8ey+NPvoYz1btdR2OEAXGkiVLqF27NkWLFsXf359vv/2WoUOH6jqsHDV37lxatGiBubk5u3btYuXKlSxZskTXYQmRr0mSKYQQIl9LSU7m6rEjpCQlUcShhK7DEaJAuX79Ol9//TWPHz/G2dmZzz77jPHjx+s6rBx18uRJ5syZw7NnzyhbtiyLFi2if//+ug5LiHxNkkwhhBD5mqIovNu9DzfPnsq15w0KUVgtWLCABQsW6DqMXPX777/rOgQhChxJMoUQQuRrBoaGVG3akqpNW+o6FCGEEEIgs8sKIYTIxxLjYom4cQ2Zw04IIYTIOyTJFEIIkW9dPxnAmgmj2Tpnmq5DEUIIIcT/SZIphBAi3wo6chAAR9eKOo5ECCGEEC/IPZlCCCHyrXe79yHoyEEqNWis61CEEEII8X+SZAohhMi37Mu6Yl/WVddhCCGEEOIlMlxWCCFEvnTt+FHin8foOgwhRC5zcXHhu+++03UYQojXIEmmEEKIfOfR3TD+WjCbnwf3JSk+XtfhCJEl8defEDH/NPHXn7y1NiMiIhgxYgSurq6YmJhgb29P/fr1+fHHH4mNjX1rcQghChcZLiuEECLfuXLUDwAn96oYmpjoNhghskBRFKL23CI5Mo6oPbcwdrVBpVLlaps3b96kfv362NjYMHPmTKpWrYqxsTEXL17k559/pmTJkrz33nu5GkNGFEUhJSUFAwP5KipEQSQ9mUIIIfIVRa3WJJluMuGP0BF1YsorX0pK6rNblWQ16sQU4oIekXQ3dXh30t0Y4oIepZZLSkktp1Y0+6bXRnYMHjwYAwMDTp8+TZcuXXBzc6Ns2bL4+PiwY8cO2rdvD8DTp0/p378/dnZ2WFlZ0bRpU86fP6+pZ8qUKVSvXp3Vq1fj4uKCtbU1H374Ic+ePfs3VrWaWbNmUaZMGUxNTalWrRqbNm3SbPfz80OlUrFr1y5q1qyJsbExR48eJSQkBB8fH+zt7bGwsKB27drs378/W8crhMg75OcjIYQQ+co/164Q/SASI1NTytWso+twRCF1b9KxV2637V4JMw87nm6/yfPj4Wm2P159BQCjMtYU/9SD5Aex3F9wFj1zA0pM9ErTRqnZDV8rvkePHrF3715mzpyJubl5umVe9KR+8MEHmJqasmvXLqytrVm6dCnNmjXj2rVr2NraAhASEsLWrVvZvn07T548oUuXLsyePZsZM2YAMGvWLH777Td++uknypcvz+HDh/noo4+ws7OjUaNGmja/+OIL5s6dS9myZSlSpAh37tyhTZs2zJgxA2NjY1atWkX79u0JDg7G2dn5tY5ZCJF3SJIphBAiX7ny/2djlq9TH0NjGSorRHpu3LiBoihUrKj9DNlixYoR///7mIcMGUL79u05efIkkZGRGBsbAzB37ly2bt3Kpk2b+OSTT4DUnkpfX18sLS0B6NmzJwcOHGDGjBkkJCQwc+ZM9u/fj5dXaoJctmxZjh49ytKlS7WSzGnTptGiRQvNsq2tLdWqVdMsT58+nS1btrBt2zaGDh2aC2dGCPE2SJIphBAiX7EqVhyLosVkqKzQqRLT6r1yu0o/9Y4k67ZlSAyLJin8OSgvFwBDR3OK9a0MgIGdWZo6M2sjO06ePIlaraZHjx4kJCRw/vx5YmJiKFq0qFa5uLg4QkJCNMsuLi6aBBPA0dGRyMhIIDWhjY2N1UoeARITE/H09NRaV6tWLa3lmJgYpkyZwo4dOwgPDyc5OZm4uDjCwsJy5HiFELohSaYQQoh85Z2OXajj876uwxCFnJ6RfpbKJYZGk3TvedoNCiTde07irWeYVCiCSk+F6j91ZrWN9Li6uqJSqQgODtZaX7ZsWQBMTU2B1CTP0dERPz+/NHXY2Nho/t/Q0FBrm0qlQq1Wa+oA2LFjByVLltQq96J39IX/Dt0dM2YM+/btY+7cubi6umJqasr7779PYmJiFo9UCJEXSZIphBAi30iKj8fQxASVnsxbJ/I+RVGI2nsLVGj3Yr6ggqi9tzAun/MzzRYtWpQWLVqwePFihg0bluF9mTVq1CAiIgIDAwNcXFyy1VblypUxNjYmLCxMa2hsVvj7+9OnTx86duwIpCast27dylYcQoi8Q67SQggh8oWE2Of8+GlPtnwzlcQ4eb6fyAdSFFKeJqSfYAIopG5PyajAm1myZAnJycnUqlWLDRs2cOXKFYKDg/ntt9+4evUq+vr6NG/eHC8vLzp06MDevXu5desWx44dY8KECZw+fTpL7VhaWjJmzBhGjRrFypUrCQkJ4ezZs3z//fesXLnylfuWL1+ezZs3ExgYyPnz5+nevbumh1QIkX9JT6YQQoh84doJf5Li44iKvI+hiamuwxEiUyoDPYoP9UT9PCnDMnoWhqgMcuc3/3LlynHu3DlmzpzJ+PHjuXv3LsbGxlSuXJkxY8YwePBgVCoVO3fuZMKECfTt25cHDx7g4ODAu+++i729fZbbmj59OnZ2dsyaNYubN29iY2NDjRo1+PLLL1+53/z58/n444+pV68exYoVY9y4cURHR7/poQshdEylKEru/HyWj0RHR2NtbU1UVBRWVla6DkcIIUQ6wi6d58yOrZRyq0Lt9zrrOhyRB+T29Ts+Pp7Q0FDKlCmDiYnMZCyEKNxe52+iTofL/vjjj3h4eGBlZYWVlRVeXl7s2rVLsz0+Pp4hQ4ZQtGhRLCws6Ny5M/fv39eqIywsjLZt22JmZkbx4sX5/PPPSU5OftuHIoQQIpc5V6lGx3GTJcEUQggh8jidJpmlSpVi9uzZnDlzhtOnT9O0aVN8fHy4fPkyAKNGjeKvv/5i48aNHDp0iHv37tGpUyfN/ikpKbRt25bExESOHTvGypUr8fX1ZdKkSbo6JCGEELkg5vEjFLlPSwghhMgX8txwWVtbW7799lvef/997OzsWLt2Le+/nzpV/dWrV3FzcyMgIIC6deuya9cu2rVrx7179zT3Dfz000+MGzeOBw8eYGRklG4bCQkJJCQkaJajo6NxcnKS4bJCCJFHrfp8KPHPn9N+9Bc4ulbMfAdRKMhwWSGEeHvyzXDZl6WkpLB+/XqeP3+Ol5cXZ86cISkpiebNm2vKVKpUCWdnZwICAgAICAigatWqWjeme3t7Ex0drekNTc+sWbOwtrbWvJycnHLvwIQQQryRB7dDeRB2i9ioJxRxKJn5DkIIIYTQqWzNLpuSkoKvry8HDhwgMjIyzVTTf//9d5brunjxIl5eXsTHx2NhYcGWLVuoXLkygYGBGBkZaT0IGMDe3p6IiAgAIiIi0sx89mL5RZn0jB8/ntGjR2uWX/RkCiGEyHtMLCyp0+EDEuPiMLGw0HU4ohDKY4O+hBBCJ17nb2G2kswRI0bg6+tL27ZtqVKlyhs9QLhixYoEBgYSFRXFpk2b6N27N4cOHcp2fVlhbGyMsbFxrrYhhBAiZ1gWLUbDbr11HYYohAwNDQGIjY3F1FQemyOEKNwSExMB0NfXz7RstpLM9evX8/vvv9OmTZvs7K7FyMgIV1dXAGrWrMmpU6dYuHAhXbt2JTExkadPn2r1Zt6/fx8HBwcAHBwcOHnypFZ9L2affVFGCCFE/hX98AH6BgaY2xTRdSiiENLX18fGxobIyEgAzMzM3uiHdSGEyK/UajUPHjzAzMwMA4PMU8hsJZkvJ4Y5Ta1Wk5CQQM2aNTE0NOTAgQN07pw6XX1wcDBhYWF4eXkB4OXlxYwZM4iMjKR48eIA7Nu3DysrKypXrpwr8QkhhHh7jv+xjkt++2n0UT9qtvXRdTiiEHrxo/WLRFMIIQorPT09nJ2ds/RjW7aSzM8++4yFCxeyePHiN/pFb/z48bRu3RpnZ2eePXvG2rVr8fPzY8+ePVhbW9OvXz9Gjx6Nra0tVlZWDBs2DC8vL+rWrQtAy5YtqVy5Mj179mTOnDlERETw1VdfMWTIEBkOK4QQ+VxyYiLXjvujqNUUdymj63BEIaVSqXB0dKR48eIkJSXpOhwhhNAZIyMj9PSyNm9stpLMo0ePcvDgQXbt2oW7u7vmnoUXNm/enKV6IiMj6dWrF+Hh4VhbW+Ph4cGePXto0aIFAAsWLEBPT4/OnTuTkJCAt7c3S5Ys0eyvr6/P9u3bGTRoEF5eXpibm9O7d2+mTZuWncMSQgiRh9w8d4qE2OdYFC1GKbcqug5HFHL6+vpZug9JCCFENp+T2bdv31duX7FiRbYD0oXcfs6WEEKI1/fn3BncOBVAbZ/3ebd7H12HI/IguX4LIUTelK2ezPyWRAohhMhf4mKeEXruFACVGzTWbTBCCCGEeC3ZSjJfePDgAcHBwUDqo0js7OxyJCghhBCFW3TkfSyL2WFoZEwxZxddhyOEEEKI15Ct4bLPnz9n2LBhrFq1CrVaDaTeq9CrVy++//57zMzMcjzQ3CTDbYQQIu9RFIW46CjMrG10HYrIo+T6LYQQeVPWpgf6j9GjR3Po0CH++usvnj59ytOnT/nzzz85dOgQn332WU7HKIQQohB58dunSqWSBFMIIYTIh7LVk1msWDE2bdpE48aNtdYfPHiQLl268ODBg5yK762QX0KFECLvOPnnJm6dP0vt9zpTpnpNXYcj8jC5fgshRN6UrZ7M2NhY7O3t06wvXrw4sbGxbxyUEEKIwklRFIIO/82dyxeIefxI1+EIIYQQIhuylWR6eXkxefJk4uPjNevi4uKYOnUqXl5eORacEEKIwiU5IYGiJZ0wNjOn/Dv1dB2OEEIIIbIhW8NlL126hLe3NwkJCVSrVg2A8+fPY2Jiwp49e3B3d8/xQHOTDLcRQoi8JTkxEQMjI12HIfI4uX4LIUTelK0kE1KHzK5Zs4arV68C4ObmRo8ePTA1Nc3RAN8GuUgJIYTuKWo1iqKgp6+v61BEPiHXbyGEyJuy/ZxMMzMzBgwYkJOxCCGEKMTCLl9g5/dz8WjeivpdPtJ1OEIIIYTIpiwnmdu2baN169YYGhqybdu2V5Z977333jgwIYQQhcuVI37ERj0lNuqprkMRQgghxBvIcpLZoUMHIiIiKF68OB06dMiwnEqlIiUlJSdiE0IIUYjYlXahSIlSuDVsoutQhBBCCPEGsn1PZkEi93QIIUTe8OKSpFKpdByJyA/k+i2EEHlTth5hsmrVKhISEtKsT0xMZNWqVW8clBBCiMIlLuYZkJpcSoIphBBC5G/ZSjL79u1LVFRUmvXPnj2jb9++bxyUEEKIwiM2Ooqln/Zkw9QvSIyP03U4QgghhHhD2UoyFUVJ95fmu3fvYm1t/cZBCSGEKDyuHfcnJTmZxNg4jEzy32OwhBBCCKHttR5h4unpqRnK1KxZMwwM/t09JSWF0NBQWrVqleNBCiGEKLiuHPUDwK1hY53GIYQQQoic8VpJ5otZZQMDA/H29sbCwkKzzcjICBcXFzp37pyjAQohhCi4nt6P4F5wEKhUVKr3rq7DEUIIIUQOeK0kc/LkyQC4uLjQtWtXTExMciUoIYQQhcPV//diOlephoVtUd0GI4QQQogc8VpJ5gu9e/fO6TiEEEIUQpG3bwJQWZ6NKYQQQhQY2UoyU1JSWLBgAb///jthYWEkJiZqbX/8+HGOBCeEEKJge2/0lzwIu4V1cXtdhyKEEEKIHJKt2WWnTp3K/Pnz6dq1K1FRUYwePZpOnTqhp6fHlClTcjhEIYQQBZmds4vMKiuEEEIUINlKMtesWcOyZcv47LPPMDAwoFu3bvzyyy9MmjSJ48eP53SMQgghChh1SgpbvpnKuT3bSUpM0HU4QgghhMhB2UoyIyIiqFq1KgAWFhZERUUB0K5dO3bs2JFz0QkhhCiQwi4GcvPsKY5tXIueXrYuRUIIIYTIo7J1ZS9VqhTh4eEAlCtXjr179wJw6tQpjI2Ncy46IYQQBVL0wwcYGptQ0ash+gaGug5HCCGEEDkoWxP/dOzYkQMHDvDOO+8wbNgwPvroI5YvX05YWBijRo3K6RiFEEIUMB7NW+HWoLEMlRVCCCEKIJWiKMqbVnL8+HGOHTtG+fLlad++fU7E9VZFR0djbW1NVFQUVlZWug5HCCGEEFkg128hhMibstWTefjwYerVq4eBQerudevWpW7duiQnJ3P48GHefffdHA1SCCFEwbHz+7kYGBlRx+cDbBwcdR2OEEIIIXJYtu7JbNKkSbrPwoyKiqJJE3mgthBCiPTFRj3l6rHDXPx7L2p1iq7DEUIIIUQuyFZPpqIoqFSqNOsfPXqEubn5GwclhBCiYHr2+BHFnF3Q19fHtkQpXYcjhBBCiFzwWklmp06dAFCpVPTp00drJtmUlBQuXLhAvXr1cjZCIYQQBYZ9mXL0+mYRCbGxug5FCCGEELnktZJMa2trILUn09LSElNTU802IyMj6taty4ABA3I2QiGEEAWCWp2Cnp4+AMZmZjqORgghhBC55bWSzBUrVgDg4uLCmDFjZGisEEKILDv+x3pCz53mnU4f4lrrHV2HI4QQQohckq17MidPnpzTcQghhCjAFEXhylE/nkaEkxgnQ2WFEEKIgizLSWaNGjU4cOAARYoUwdPTM92Jf144e/ZsjgQnhBCiYIi4cY2nEeEYGBvjWruursMRQgghRC7KcpLp4+OjmeinQ4cOuRWPEEKIAijoyEEAXGvVxcjENJPSQgghhMjPspxkvjxEVobLCiGEyKqU5GSCA44AULmhPEtZCCGEKOiydU/mC2fOnOHKlSsAuLu74+npmSNBCSGEKDjCr18lLjoKUytrSnvIdUIIIYQo6LKVZEZGRvLhhx/i5+eHjY0NAE+fPqVJkyasX78eOzu7nIxRCCFEPuZYvhIDfljBozu30dPX13U4QgghhMhletnZadiwYTx79ozLly/z+PFjHj9+zKVLl4iOjmb48OE5HaMQQoh8KjE+nsf/3MXU0pIynrV0HY4QQggh3oJsJZm7d+9myZIluLm5adZVrlyZH374gV27duVYcEIIIfK3pLhYNkwZR2J8vK5DEUIIIcRbkq0kU61WY2homGa9oaEharX6jYMSQgiR/yTEPifs0nlio6NISojn+dMn7Ph+Lgmxz9mxcA6xUanrhRBCCFGwZSvJbNq0KSNGjODevXuadf/88w+jRo2iWbNmORacEEKIvCk5MZF7166SGBcLwN2rl1nctysbp0/AwMiIpxERrBg1kDuXLwBw5/IFfh35CU8jIkhJTtZl6EIIIYTIZdma+Gfx4sW89957uLi44OTkBMCdO3eoUqUKv/32W44GKIQQQrcUReFh2C0iQq4TceMaESHXeXjnFuqUFDp9MYUynrUo5lQaACs7e24FnqWMZ00+Xvgz27/7hjuXL+Dk7kG7keMwNDZG3+CNJjYXQgghRB6nUhRFyc6OiqKwf/9+rl69CoCbmxvNmzfP0eDelujoaKytrYmKisLKykrX4QghhM4oisLT++FEhFzHwqYITu4eACwd2IuYJ4+1yppZ29C4V3/cGjQGIO5ZNKaW2n9DY6Oi+HXkJ3y88GfMrKzfyjGIwkOu30IIkTdl++dklUpFixYtaNGiRU7GI4QQ4i2KefyIiJDrWBe3x650GVKSkvAdPRh1SjIVvRpqkkznKtV49vgRDuXKp75cK2BZ1A6VSqWp678JJoChiTFdp3yDobHxWzsmIYQQQuhWlpPMRYsWZblSeYyJEELkPfExMUTcvI5tiZJYFSvOs0cP+XlwHwBqtutI4579MDAywsG1AkpKimYILEDroZ9lq01DYxNsS5aSIbJCCCFEIZLlq/6CBQuyVE6lUkmSKYQQeUD4jWDuBV8lIuQaESHXeBoRDkCT3gOo0cYHC9uiWBSxxcTSCnNrG81+H079RquH8k1JgimEEEIULlm+8oeGhuZmHEIIId5A5K2bRNy4hoGxMZUbNgHgyBpf7gRd1Cpnbe+ASi91YnGVSkX/xcvRN9B+JFVOJphCCCGEKHze+OflF/MGyZcSIYTIfYqi8CT8HhEh1zCztMKlek0A/lowi6cR4RR3KadJMktXq4GRmRkOZVPvo7QvVz7NfZP/TTCFEEIIId5UtpPM5cuXs2DBAq5fvw5A+fLlGTlyJP3798+x4IQQojBTFOX/E/Ncw6pYcezLuqKo1az+YjjJCQmUrVlHk2SWrlodq2LFKVHRTbP/Ox0+0FXoQgghhCjEspVkTpo0ifnz5zNs2DC8vLwACAgIYNSoUYSFhTFt2rQcDVIIIfKzlOTkLN+XeO/aFW5fDCQi5Dr3Q67z/OkTAKq1bIt9WVf09PUpWbEyifFx2Jdx1ezXvP+QXIldCCGEEOJ1Zes5mXZ2dixatIhu3bpprV+3bh3Dhg3j4cOHORbg2yDP2RJC5JbE+Hii7kdg4+CAobGJ1rbwG8H8czWIpPh4vN5P/Xu67+fFXDiwW1NGpadHMafSVKz3rqZnUlEUuUVBCOT6LYQQeVW2ejKTkpKoVatWmvU1a9YkOTn5jYMSQoiCIjkhgQ1TxtF3wU/cu3aV6AeRVG3aEoCATesIPXcaI1NT6nbqikpPj9LVPEmMj8OhXAUcypWneJmyaZJTSTCFEEIIkZdlK8ns2bMnP/74I/Pnz9da//PPP9OjR48cCUwIIfKzxPh4khPi2b5wDgmxz9mx6FtaDRqJgeG/E+24VKuBvoEBDuUqkJychKGRMRXeqU+Fd+rrMHIhhBBCiDeTreGyw4YNY9WqVTg5OVG3bl0ATpw4QVhYGL169cLwpS9R/01E8yIZbiOEyElJCQk8ibjH71O+ICH2uWa9sZk5XafMxrakkzw7UogcINdvIYTIm7KVZDZp0iRrlatU/P33368d1NsmFykhRE64e/Uyx35fQ0Lsc97t0ZciDiXY/eN33Ll8ASd3D9qNHIehsXGa4a9CiOyR67cQQuRN2UoyCxq5SAkh3kRC7HP+WjCb2xfOAaBvYEDVZt7U6/IRSoqaX0d+wscLf8bMylrHkQpRsMj1Wwgh8ia97Oz04MGDDLddvHgxy/XMmjWL2rVrY2lpSfHixenQoQPBwcFaZeLj4xkyZAhFixbFwsKCzp07c//+fa0yYWFhtG3bFjMzM4oXL87nn38uExAJIXJdUkI8AEamZiTEPkdPXx+P5q34eOHPNPt4EKYWlhiaGNN1yjcYGhvrOFohhBBCiLcjW0lm1apV2bFjR5r1c+fOpU6dOlmu59ChQwwZMoTjx4+zb98+kpKSaNmyJc+f/3sP06hRo/jrr7/YuHEjhw4d4t69e3Tq1EmzPSUlhbZt25KYmMixY8dYuXIlvr6+TJo0KTuHJoQQmYq8dZOt305n/eRxmseJtBgwlI+/W0qLAUOxKlZcU9bQ2ATbkqVkiKwQQgghCo1sDZedM2cOkyZNom/fvsyfP5/Hjx/Tq1cvLl68yNKlS+nYsWO2gnnw4AHFixfn0KFDvPvuu0RFRWFnZ8fatWt5//33Abh69Spubm4EBARQt25ddu3aRbt27bh37x729vYA/PTTT4wbN44HDx5gZGSUpp2EhAQSEhI0y9HR0Tg5OclwGyFEluz5aSGXDu5DpdKj+4x5OJQrr+uQhCiUZLisEELkTdnqyRw7diwBAQEcOXIEDw8PPDw8MDY25sKFC9lOMAGioqIAsLW1BeDMmTMkJSXRvHlzTZlKlSrh7OxMQEAAAAEBAVStWlWTYAJ4e3sTHR3N5cuX021n1qxZWFtba15OTk7ZjlkIUfA9+ucOe35aSEJsLAB1O3WlUv1G9J73gySYQgghhBD/ka0kE8DV1ZUqVapw69YtoqOj6dq1Kw4ODtkORK1WM3LkSOrXr0+VKlUAiIiIwMjICBsbG62y9vb2REREaMq8nGC+2P5iW3rGjx9PVFSU5nXnzp1sxy2EKNhCA8+w8rMhXDq4j3O7/wLAurgDbYd/TtGS8gOVEEIIIcR/ZetBbf7+/nz00UfY2tpy4cIF/P39GTZsGDt37uSnn36iSJEir13nkCFDuHTpEkePHs1OSK/F2NgYY5mEQwiRgajICECFdXF7SlWugrmNDfblKlC2Rm1dhyaEEEIIkedlqyezadOmdO3alePHj+Pm5kb//v05d+4cYWFhVK1a9bXrGzp0KNu3b+fgwYOUKlVKs97BwYHExESePn2qVf7+/fuaXlMHB4c0s82+WH6TnlUhROET/TCSfT8v5teRn3J4rS8AhkbG9J67hA6ff0Vxl7K6DVAIIYQQIh/IVpK5d+9eZs+ejaGhoWZduXLl8Pf359NPP81yPYqiMHToULZs2cLff/9NmTJltLbXrFkTQ0NDDhw4oFkXHBxMWFgYXl5eAHh5eXHx4kUiIyM1Zfbt24eVlRWVK1fOzuEJIQqZZ48fsn/5jywf/gkXDuxGnZJCYlwsKf9/FJKJhYWOIxRCCCGEyD9ea3bZNm3asG7dOqytUx8oPnv2bAYOHKi5Z/LRo0c0bNiQoKCgLNU3ePBg1q5dy59//knFihU1662trTE1NQVg0KBB7Ny5E19fX6ysrBg2bBgAx44dA1IfYVK9enVKlCjBnDlziIiIoGfPnvTv35+ZM2dmKQ6ZnU6Iwivy1k3WfvUZKUlJADhX8cDrgx6UquSu48iEEJmR67cQQuRNr5Vk6uvrEx4eTvHiqc+As7KyIjAwkLJlU4eQ3b9/nxIlSpCSkpK1xlWqdNevWLGCPn36ABAfH89nn33GunXrSEhIwNvbmyVLlmgNhb19+zaDBg3Cz88Pc3NzevfuzezZszEwyNotp3KREqJwiY2OIj7mGbYlSqGo1awaOwxjcwvqd+mBk7uHrsMTQmSRXL+FECJveq0kU09Pj4iICE2SaWlpyfnz57OdZOYVcpESuSklORn9LP7gIXKXoij4b1jN2Z3bKF6mHF2nzEalUhH3LBoTC8sMf/gSQuRNcv0WQoi8KduPMBFCZC4xPp7H/9wlKSFe16EUaopaDaSOnngaEU5SQjzJiYkkPH8OgKmllSSYQgghhBA55LWSTJVKleaLmHwxEyJ9iqKQFB/HhinjSIyXJFMXEmJjCdi0Dt8xQ0hKTACgXpeP8Pl8Ij1mzpcJfYQQQgghcsFrjeFTFIU+ffponjEZHx/PwIEDMTc3ByAhISHnIxQiH3oe9RR1chK7flhAQuxzdiycQ+shozGxsMDQ2ISU5CT0DQwzr0i8kfP7dnJs4xoArhzxw6OZN7YlSmJboqRuAxNCCCGEKMBe657Mvn37ZqncihUrsh2QLsg9HSInJcXH8+R+OL9P+YKE2Oea9cZm5nSd8g22JUuxedZknj99gmvtujT4sJcOoy1YkhLiCdy7k/J16mFj70BiXCybZ0+hunc7KtZtgEpP7hAQoiCR67cQQuRNr9WTmd+SRyHelsS4WNQpakwsLFCr1SQ8j6H33B/Y9cN87ly+gJO7B+1GjMXQxARQuHftKsmJCVjb/ztLcsAf60h4HoNzleqUrVFbdweTDyUlJnBh325O/rmR2KinPLobRqtBIzEyNePDqXN0HZ4QQgghRKEiU14K8QbUKSlc/HsPxzaupXydejTvPxhjMzOKObtgamFJuxHj+HXkJ7QbOQ4zK2vNfgN++JW7QRcxsbDUrLt0cB/RDyIJu3hek2TevhCIWp1CyUqVMTIxfevHl9clJyVx8e89nNzyOzFPHgNgZWePU+WqOo5MCCGEEKLwkiRTiDd0bvd2YqOecifoIslJSRgYGmL6/+TR0MSYrlO+wfD/9zG/YGZlTYW6DTTLilpNw269uXP5olbv5vHN67l75RJ6+vrYlyuPs7sHTpU9KFGxEobGJm/nAPOwa8eP8vevPwFgWdSOup274t6omdzvKoQQQgihQ691T2ZBJfd0iNdxPzSE4GOHadi9DyqVitsXAnl87w4ezVun+zzMN3lO5v5flhAaeIboB/e11jfq2Y9a7ToCcO/aFYqXccXAsOAnVuqUFIIO/41d6TLYl3VFnZLCpq+/okLdBlRp2rJQnAMhxL/k+i2EEHmTJJnIRUpk3bk92/l7xVJQFDqOm/zW7p2MirzPncsXCLt8gTuXL9Bh7CTsy5QjKvI+vwzrh4GhEe9+1BfPVu2B1J7RgjbJTUJsLL+NH8HTiHBcqtWg85fTdB2SEELH5PothBB5kwyXFSITCbGx6BsaYmBoSOmqnujp6VOhbn2KOZV+azFYF7fHungLqjRpwcu/C0U/uI+ZtQ2xUU+xLGoHpE6C8/PgvjiUdcWjRWvK1/Z6a3HmNLU6hWcPH2Jd3B5jMzNsSzqR8Pw5patWL5CJtBBCCCFEQSA9mcgvoSJ9L0/qU7t9J2q17wRA9MMHWBWz03F0/1IUhcf/3MGymB1GJqaEXTrPxukTAGjS5xNqtH4PRVHYvWQBdqXL4OTuQfHSZfJ8gnbj9AmOrltJUkICH3+3FH0DA549foixmblMgiSEAOT6LYQQeZX0ZArxH4qicPPsKQ6vWcHjf+4AEHz8KDXbdUSlUuWpBBNApVJRtJSzZtmpclV6zfmeO5cvULZGHQCe3g8n6PDfmjIm5haUqlwFJ3cP3Bs1w9jM/K3HnZnwa1d4dDcMY3NzHt65jX2ZcljaFtN1WEIIIYQQIhPSk4n8Eir+9TQinH3Lvifs0gUATCyt8OrcjWot0p/UJ7+IjXrK5cN/c+fyBe5euUxSfFzqBpWKIb+sw8TCggdht7gXHISTuwdFHEuiUqneWnyKohB67jQntm6k/chxWNgWJe5ZNIF7duDZuj0m5hZvLRYhRP4h128hhMib8u+3ZiFygaGJCeE3rqNvYECNNj7U6fBBgUhwzKxtqN2+E7Xbd0KdksL9mzcIu3SeZ48eYmKRenzXAo5wfPMGAHp/u5hizi7Ex8QQH/MMa3uHXEk6FUXh9oVzHPt9DeE3ggE49ddmmvQegKmlFV7vd8vxNoUQQgghRO6SJFMUaolxsZz88w9UenrU79IDc5sitBn6GXaly2Bd3F7X4eUKPX19HMtXxLF8Ra31Ng4lcHL34EnEPc3w22snjrLv58VYFrWjw9iJFHcpi6IoOZJw3r16maPrVvLP1SAADIyMqe7dltrvdX7juoUQQgghhO5IkikKtT9mTubetSvoGxjg0cwby6LFcK1dV9dh6YR7o2a4N2qGWp2imRQo5vFj9PQNiHn8SJN0375wjv3Ll+BU2QNn96o4uXtgYVs0w3ozek5oZOhN/rkahIGhEdVatqb2e+9jblMkdw5OCCGEEEK8NZJkikJFURQiQq7h6Jrai1ezrQ9xz6Jo2KPvKxOlwkRPT/9/7d13nBT1/cfx15Tte3uN6xxwlKNKRwQpYgVjAbFh1xhjr1Gj8RdNNbbYjYmJGmOJGkvsDWxERKSLFOn1Dq63rTPz+2P29u64O0C9Bnyej8c+tkzZ+c7t3e17Pt/5TuLx+NPOYsyJp7Br84bE4EBbViyjsriIyuIivvn4AwBSc/LoN3Y8E2ed32RdkVCIyuIiUrKz2bVpI/P+8zyTzrmIjB69GHrUcdSWlzJi6omy74UQQgghDiASMsVBo3TrFuY89Rc2f7OM0/7vj/QYMpR+Yw+nz+jD9utBfdqbw+0mt3Bg4vmh008nb+BgtqxYzuZvlrJz43rKd2yjfMe2xDxz//0MqTl59Bo6ghfvuJkL73+cJe+/xcali3B6vJx43S/RnU4mnnVBJ7RICCGEEEK0J/lmLQ4aRizK5hXL0RwOyrZvpceQoSiKIgHze3J5vfQeMYbeI8YAEKqpYevKbxIDCFmWRc+hI0nOyOTth+8lXFfL2w/dw7QrrmfMSTNxJ8kIkEIIIYQQBzK5hAkyBPqBKhKsY8Ebr5Ccmc2QKccAsOyj9+g5dMQBO6hPV2DEYpRt28KLd/yScF1t4nWX18cZd9xFWl53CfZCiDYh/7+FEKJrkpCJ/JM60JiGwfI5H/DFy89RV1mBNzmFnz70BE63p7M37aARDYeIhsO89cBdbFmxjPzBQznh2ptxuFw4XO7O3jwhxAFC/n8LIUTXJOUEccCwLIsNS77ms2efonTrZgBSsnOYdPaFEmw6mMPlxuFyc8I1N/PktZdwwrU34w0kd/ZmCSGEEEKIDiAhUxww6ioreOO+P2JEo7iTAoybOYthx0xF0x2dvWkHLYfbxRl33IXD5ersTRFCCCGEEB1EQqbYr1WXllC8YR19R4/Fl5LKoSefSjQcZuyM03H7/J29eQc9h8st52AKIYQQQhxk5Juf2G8tfPu/zP33MyiKwkUP/g1/ahrjTzu7szdL7EYCphBCCCHEwUXt7A0Q4vuwTDPx2OXzEYuEySzoTSQY7MStEkIIIYQQQtSTEoPYLzQe1Oe4y64hp29/Bk2agi8llV7DRqIoSmdvohBCCCGEEAKpZIr9RMmWTbz2p99QunUzX776IgCqqlEwfJQETCGEEEIIIboQqWSKLqu6tISqkl3k9R9IRo9eDJw4BX9qGodOP62zN00IIYQQQgjRCgmZosuJBOtY8MYrfP3W63gCAS68/3EcThfTrrheqpZCCCGEEEJ0cRIyRZdhGgbL53zAFy8/R11lBQCBbhkEq6pwdMuQgCmEEEIIIcR+QEKm6BKMWIznbr2OXZs2AJCSncOksy+k75hxEi6FEEIIIYTYj0jIFJ0qVFOD2+9H03W6DxxCdVkp42bOYtgxU9F0R2dvnhBCCCGEEOJ7UizLsjp7IzpbVVUVycnJVFZWEggEOntzDgrVZSX879/Psm7hfC564K94kgKEamsAcPv8nbx1Qggh9gfy/1sIIbomuYSJaHdGLNbstbULvmTFpx8Rqqlm/aIFgB0uJWAKIYQQQgixf5PusqJdRUIhKouLSM7KYuXnn5DXfyDdevRi6FFTKfpuNcOPO4Gcfv07ezOFEEIIIYQQbUQqmaJdxcJhXrzjZkI1NWxbtYLPnnsKAE3XmXblDRIwhRBCCCGEOMBIJVO0CSMWpba8nJryUqKhEMmZWehOF+88ch/hulree+x+pl52LYYRw7IsGTFWCCGEEEKIA5SETLFHlmURCdbh8voA2LpqBZuXL6W2vIwpF/4c3eFg1Ref8faDdyeWueyJ56gpL+PZW64jXFcLwJYVy3jmpqs44467MA0DTZePnhBCHPCideDwtv5cCCHEAUm6yx7EoqEQ5Tu2sWXFMlZ+/jEL3niFFZ/OTkx/+6F7ePCcGTz9iysSr21evpR5/3meZbPfo66iHABPkj2in6brBDKy+OzZp8A0Of++x8gfPBSA/MFDuejBv5GSnS0BUwghDgbRIHz+Z/u+pedCCCEOWPJt/wBkGgbRcChRffzuqy8oXr8W0zCYdPaFAPzvpWf58pV/N1u2+8AhDJ58FACqqmLEYtRVVGCZJoqqktuvP4ccdRz+1HR0pxOAvP6DuOyJ5/AkBZp1gz3hmpt58tpLOOHam/EGktuz2UIIIbqKaJ0dKD+7B7YthJMegTeuhHVz7OkTr5eKphBCHMAkZLYzIxZrs8qdZVmEa2upKS+lpqyUmvIyaspKyerdl4LhowD41y+vYdfGDfQcOpyZt/4WgFX/+4w1X85Fd7mYeNYFKIqSqD46XG78aen2LTWNjF69E+93+JnncvgZ5+JLTUVR7aJ3r+Gj6BV/r3q605kInLtzuF2cccddOFyuNtkHQgghujDLgpI19m381XbAXDcH7h9kT+9zJEy8ARyezt1OIYQQ7UpCZjuqv3xHSnY2Dpd7j/PGIhFMI4bTYx/ZXfrhu5QXbcefmsboE2YA8MZ9f2TtgnnNlh12zPGJkKkoCpZlUhvvygpQMHwU3uQU/GnpdkVS0xgy5RgGTz4al7f1I8mBbpnfu827c7jcpOV1ly6yQghxINuxDOY/Dus+hurt9muTboTj74GHGx2YPOkRCZhCCHEQkG/+7aj+8h0XPvBX6iorKNmyOVGB7Dt6LFm9+xIJ1vHEVRcTqq5i1E+mc8R5FwOw+L03Kd26mew+/RIhs767qdvnT1Qffalp5A0YlHjPE665GYfbjScQSLw2ZMoxDJlyTJNtc7o77p+8BEwhhDiARIOw6Qv7cV/79AqC5bDkOfux5oLDLoPDr4WXzm267BtXwpnPS9AUQogDnHz7bwfRcIhoKMxbD95FuK6Wtx+8m6mXXYvucLDso3fZuXE93kCArN59cbg9xEIhgCbVx4ETjiBYXUVaXn7itYlnX8ARF/wMh7P1rqcp2Tnt1zAhhBAHH9OEomWw/mO7Urn5SzDC0H1MQ8jscRgcfg30PgJ6jAMs+5zMdXPsLrKNz8n8/D45J1MIIQ5wimVZVmdvRGerqqoiOTmZyspKAo0qgD+EEYtRtm0rL95xc+LyHQAur4/T7/gTgW4ZzH3hnxQeNoEeQ4YBULZ9K55AMm6fX64fKYQQomvYPB+++ius/wTqSptOC+RB36PhxAehtf9b0WA8UMbPwdz9eRtoy//fQggh2o6ETNr+n1Q0HCIaDvPWA3exZcUy8gcP5YRrb8bhcu313EwhhBCiw4WqYONccPqg92T7tZVvwovn2I+dfug1AXpPsSuT3fq1Hi4ba+frZErIFEKIrkm6y7YDh8uNw+WWy3cIIYTomowYbF9kd39d/zFsXQBmDPoc1RAye02ESTdBnyl211jN8f3fZ/dAKV1khRDioCAhsx3J5TuEEEJ0Kes+hgV/hw2fQ7iy6bTUAsgc2PDckwJH/qpDN08IIcSBQUJmO5LLdwghhOg0dWX2+ZRJ2dBzvP1a1XZY9Zb92J1iVy17T7Grlam9OmlDhRBCHGgk/bQzCZhCCCE6RCwMW+Y3dIHdvgSwYPCMhpDZ9yg48jb7vMqc4aBqnbjBQgghDlSSgIQQQoj92aq34esn7WtXRuuaTssYCBkDGp4nZcOkGzt2+4QQQhx0JGQKIYQQ+4vqIrsLbHo/6D7Kfq1iM6z9yH7sy7S7vvaeYl+zMiDXThZCCNHxJGQKIYQQXVWk1q5Q1neB3fmt/fqoCxpCZuFUMA07XGYO2rdLiwghhBDtSEKmEEII0dUsexkW/dM+x9KINJqgQM4w6FbY8FJaAYy/ssM3cV8EIzE0VaU6FCXJ7SBmmnid8tVDCCEOdPKXXgghhGgv0bqm14bc/TlA+Sa7Spk7EnKG2q+VrYeNn9uPk/Ptrq99pkDBEeBL74AN//HCUYO/fbaef87bSFUwRsCjc/64Xlw6uQ8uhww4JIQQBzIJmUIIIUR7iAZh7gMw4TpweJo+37EUlr1kh8uy9fb8469qCJmDTgZvmn1uZXqf/a4LbDASI2xEuOboQq45urDJtIpgHYbllIqmEEIcwOQvvBBCCNHWonVEYmGcU25teM3hgSm3EgmW4/R1g6//Yb+uaNB9jD2YT73MAfZtP2JZFpXBKCXVEfLTPaQ4vYx5dgwxM5aYR1d1FpyzgEjM7MQtFUII0d46NWR+9tln3HPPPSxcuJAdO3bw2muvMX369MR0y7K4/fbbeeKJJ6ioqODwww/nL3/5C/36NfwjLisr46qrruLNN99EVVVmzpzJgw8+iN/v74QWCSGEOGgFK6B0HZR+B5aFc/isVkMWH/wac8zPMAomo/Q6HN2bRsSIEAxXoikafqefiBGhNFiKoihk+7KJmTE2Vm7EsAwKUwtRFIUVpSuIGBH6p/bH6/CyomQF5eFy+qf2J8Obweqy1Wyq2kRBcgH9UvuxoXIDS3YuIdefy9icsRTXFvPR5o9IciZxUp+TCMaCPPvts5iWySVDL0FRFJ5Y9gRlwSqOzjuVSNjPf9f/m03VG8lSJhEN5vFd7SeUGN9QVzGAUMVgenbfzKDClfzl2IeImTFiVkP7iWfL6lCUdL+rY38+QgghOkynhsza2lqGDRvGRRddxCmnnNJs+t13381DDz3EP//5TwoKCvi///s/jjvuOL799lvcbjcAZ599Njt27ODDDz8kGo1y4YUXcskll/D88893dHOEEEIc6GIR0J0Nz9/+BRQth9K1UFfSMJuqow+f1WrI4uSH+dP8P/LCglu5JHwJV424ite+e43fz/89R/U4igemPMCyXcu48P0L6RXoxZsz3qQmUsOMN2YAsOTcJWiKxhUfXUFpqJRXTnqFwtRC/rzwz3xV9BV3T7qbaQXTeOW7V3hh1QtcMvQS+qX2Y0HRAn735e84qsdRjM0Zy/qKTfzpqz+R7clHrxvDxvKd/GXDQwB88tUh7KyKUJzyFIpezV/fScYM5+Dp8SG6bx0LtqUQq1JxZa3CmbYAs9YPDCZCCV8Wfb7H3ZjkdrTFT0MIIUQX1akhc9q0aUybNq3FaZZl8cADD3Dbbbdx8sknA/DMM8+QlZXF66+/zplnnsnKlSt57733WLBgAaNHjwbg4Ycf5vjjj+fee+8lNze3w9oihBDiAGGaULXVDo6l66Dku/jj76ByG9y6ze76CrB5HhR/QxT4wOdlYVIqt7gL0AecuNe3URXVfjvLTp6qaj83LAOwq54uzYVTs0OtpmqkulJRFRUTEw2NvKQ8fA4fmmIPpNMj0IOqSBUe3cfOqhC6kUFv/yFsLnbx5w9Ws7wsRMA6hK9Wexg590MqoltxZgxlc2kSly9aBEoEV/ZosFTmFZUAGk5rDIoawaMmkZXhw+mciFM7hIFDRtM/rZBqRaHKHM6Y8cM5otdYttUO4Mtt/diTmGniRP2+PxkhhBD7CcWyLKuzNwJAUZQm3WXXr19Pnz59WLx4McOHD0/MN3nyZIYPH86DDz7Ik08+yQ033EB5eXlieiwWw+128/LLLzNjxowW3yscDhMOhxPPq6qqyM/Pp7KykkAg0C7tE0II0cXUldnhESD/UPt+60J4+niIhVpf7tL/Ec3sz/+2/Y8l377E1Tn24DyTPruKykgV/5r2L4anFoLDy4hnRjSpZOqKzuLzFkO0jjogZsVwaS5cmgvDNLCw0BQNpZWBfizLoqIuSnF1iKLKEDurwhRXheLPw+ysDlFcFWJXdRhzH/+7O3WVrICLrCQ3WQE3mQEXWQE32Y0eZwXc+F3f/7h0q92F20hVVRXJycny/1sIIbqYLjvwT1FREQBZWVlNXs/KykpMKyoqIjMzs8l0XddJS0tLzNOSO++8k9/85jdtvMVCCCG6pPKN9miuJd/Fz5mMVyWD8QOUvSbCBW/ZjwO5dsBUHZDWG9L7QnofYmm9WazDcqOai7IGgxnjps9uIhgLMm3MNfRP68/MwlMxTINUd2riMiW6qjd0ka1/DuDwstuFTAhGLTswJm52gKwPkkXxxxFj3wbNURXISHLFw6K7SZDMSm54nuJ1tBpqf4yIEWkxUEaMSKI6K4QQ4sDUZUNme7rlllu4/vrrE8/rK5lCCNGm9uUaieLHMw2o3GKHx5K19v3Q0xuqkwv+AV881PKygTzwNzpYmZQNVy3CCHRnVeVavi37ltMKTyMSreOSFw4nZsU4pnAG+Un5/KT3T1BQEoHpulHXJVYTjMSImtEWQ1ZVKMiWsghPfLbeDpLVIYorQ9RGjH1ucprPSWaSi+xkdzw4uuJB0q5AZgVcpPtdaGrnXfqktSApAVMIIQ58XTZkZmdnA1BcXExOTk7i9eLi4kT32ezsbHbu3NlkuVgsRllZWWL5lrhcLlwuGdVOCNGOokH4/M8w8YaGayQ2fi5+nI/vhOJv7EBZth6MSNPpKT0aQmbOMMgbHa9K9oVu8fu03uD0AXY31I1VG1lTvobjeh1HdaiCWW/PwsJiSv4Uunm6MaXHFByqI9H98/ZxtxOOGRRXhvlyfSlFlSG2VwapCka55qhCJt39GTWh5sHR79b44pdH8dl3JZTVNt3uJJe+W3fVeMUxHiCzAi4ykly4dK3t96kQQgjRRrpsyCwoKCA7O5vZs2cnQmVVVRXz58/nsssuA2DcuHFUVFSwcOFCRo0aBcCcOXMwTZOxY8d21qYLIeDgruJF6mDun+Gze2DbQjjpIXjjalg3x54+8fqDY1/8kM9ApLZRl9ZGt7L1cP0qcNgji7PyDdj5bcNymssOjfUBsj5gAhxyqn3bzc66nazdtZTxeeMprivmpNdPQlVUxueOJ8WdwsisUeh4+N+6rRAL048rKCoP8sf/llJUuY0dlUFKaiLN1ts/K4mzx/akoi7WbBpARV2MqmCMW6YNwKmrZCa5yU52k5nkwvcDznsUQgghuppO/W9WU1PD2rVrE883bNjAkiVLSEtLo0ePHlx77bX8/ve/p1+/folLmOTm5iYGBxo4cCBTp07lZz/7GY8//jjRaJQrr7ySM888U0aWFaIzddUqnmXZ2xIN2oEnGoRobdPnvSaCJ8We/5tX7SCTWKbxcnX2vEfcbM+75St4dqb9esEkOPUpO2CumwP3D7Hn6XNkwz54+gTYusAOR7oTdDdoTtBd9v0hp8L4q+zlti+G/z3UME13xR+7Gl4bdwVo8ctCrPnAPq+w8fz18+ou8HUDT6o9rxEPQlob/zvY02dAdULFRrv6mDnQnn/HUnhhFlRta32d5Rshc4D9eOyldhvT+9ihMjkf1D1X9yrDlWyo3MDwzOGsK9/I9DdORFec/GrIy5RUWwS0HmB4Of2JD9lVHqCkxg6mH7ENaH27XLpKboqH7ICbnBQ3vbv5yExyEfDoVAWbB82ARyfN5+S00XKahhBCiANTp4bMr7/+milTpiSe158nef755/P0009z0003UVtbyyWXXEJFRQUTJkzgvffeS1wjE+C5557jyiuv5KijjkJVVWbOnMlDD7Vy7o0Qov1F6+wwkajiPQJvXLnvVTzThPINewiDQeh3LKT2tOdf/h9Y/3F8WqhpCIwG7a6Sp/7Dnrd8Azw0Ys/b/7OPIW+k/XjFa3bFrDX1QQ1A1SFcZT9eNwfmPQLH3wMPj2qY56SHG0J2NGiHpFgIGga7btBzfMPjyq2w4tU9b/e4Kxoev3ezXflrzZTbYPKN9uMlz8Kb14CitRxKPalw8YcNy758oR0Odfdu88eD8oDjIaN/08/ACQ/AW9c2fAaGnWnvl95T4LzX7de86Q0B05ve0LU1vQ+k92vo3lpv1PmtNi9qmBRXhdhUVsm3uzZghrNYXbaWD6tuRLFcOLf9ntKaKN4+yYRjSdz42lysaDpwKaDG46T9Q3HpKjnJdqUxN9lDToqb7GQPuY1ea2ngnGAkxoXjC3hw9nfNtu/C8QVyCQ8hhBAHtE4NmUcccQR7uoKKoij89re/5be//W2r86SlpfH888+3x+YJ8ePs791FTSMehMIQC9rBovGX/LWzIVJjB7tYPODFQvbAKYdf06iKN8iev8+RdmXug9th4+eNwmAQUvLh8nn2fEYEHh6552078/mGkLl1ASx+tvV5GwfBxvtfd9uBz+GN38cfNx6UpO/RdnuazBe/192Q0rNh3sxBcNUie5oryQ6d/z6r6ba8cZW97Q4PnPWSHZxjEXu/GWH7cf19cvem6556V8O0luZXG/05zx0Jvszd5onfjHDiPETAng5gGfGfSd1u+y+t6fM17zWfp7GUHpA7wq5Y1n8GHhxqT+tzJIy7Ev5zob3/Glcek3Lhpx/aYdKb1vK6sQPkzuowOyqC7KgMsaMyfl8RYntlDdtriimt9KE4t+Pt9RiW6aH2u1sBC3+hGyPmpzpYgmWlEN10EzmBJHLy3eQke8hJdsdvHjtApnhI/YEjr3qcOpcf0QeAp77YQFUwRsCjc+H4Ai4/og8uh5xTKYQQ4sDVZa6T2ZnkOluizUWD8Pl9u3UVvO/HdxeNhaGutKEKtnvAi4Vg8IyGL+9fPQFV2+PzBhvdx4Pj0DNh+Cx73uX/gfduaZjHjDZ9b6ffvgh9vT/1hFBFy9s56UYYcW5DuAC4aiEs/bdd3dpdcj5c94392LLsdeuuhlDn9DYNg+Ougvwx9vxrZ8OOJc1DYP1jT1pDF0vTtNute0BtxypS42punyObVnMn3di1zsmMReyDBfUBdPdQCtDr8Ib5lzxvt69xwG08/7AzoftoYoaJUrkF7aGGz4Bx9VIs00DXnfaorrv9DGL1AbJJcAzGB9QJUVQZ3O36jxaKVodl+FDdW/H2eALL8FO77kacuomr7+3o+DjM9Vt6peaQ6o9RkJaRCJNpPme7XLqjsbpIDF1VqQ5FSXI7iJkmXqecd9lW5P+3EEJ0TfKfrr3s71Us8cPtPujL7l0Fx1xsV8vqqzWzfwfbF+0WGBsFx2GzYNqf7HnXfwrPn7bn9y88zq6kAXz9ZNPBUXaXN7rhsWlA7c6W59OcTSt8AN1HQ7jGHohF9zTc5wyDEWfDS+c1nf+dG+GMZ6FwasPvQyIMNqqsKQrcsnnPbWys71H2bV+oatMqXntxeO0DCoA18QaCpgPPmc+jtMWBhramO0FvvXLYzPCz9jpLOGqgmWG0t69t8rr29nXETn+OnWGVN/63ke0VIYqqgvZ9ZYid1aFGAbIVSgSH5qJbtyJCqU/iVgOcnPFn0pMKeGT9X3C7wrxx42gKUjPZGRxDljer3YPkntQHynS/PaK5dJEVQghxMJCQ2R666qAnHSwYiaEdKEfwY2Go2Rm/FUNNUaPHO+3ujEf+yp63aqvdJXBPXQWn3tUQMrcvbgigLak/zw/sIKfq8fPh3A3dNhsHPavRhdoPOdXevibzNrrPHNQwb79j4NK5TQOjw928W2O9c15peXvrq3jr5jSv4s29v2tV8dpRRHESHnM1v/j3Ct5fUcxxg7O4d/rVuBQnnXWVwJhhEjFMIjGTcGz3e4NIrPn0SMwkbOw2z27LRhpNd+oqj5w2EPV/DZ+B4LQH8bx7Daybg/6/P9NtwvU89sm6ZpfvAHBoClkB+1zH7GQ3WckO8pJ9hPX1/GfTvaR50njhJ89SESln8ov3Y2gRrjyqO36nn6OGvErPQE+0+Oc129f6payEEEII0X6kuyxt3N1m925yJz4Eb17d0E1uwnWtf2k/gISjBo99sq5rn4tkWRAsjwfFeFisLmp4fPg1kB0fFfT1K+wBUlrTcwJc+Lb9uHIbLH3B7rba+NzCq5dAyRrYONcepCUp/gV47Wyo3RUf+XP3gOexw6ivW8M2d2JVZp/FuwcnqnhqtGtW8dpJMBLj8U/XtzjoyzVH9ePccT0pqgztU8CLGCbhqJEIei1Nb7yOcGKZhmn10/daJWwD/bOS+NdPDyXgMHDPu5/QuOt49POtXDGxe+J5raHz18/WowDZ8XMgc1PsgXTSvU40TWVR8SL+9NWfSHOn8fgxj7OtZhtTX5mKU3Uyd9ZcPLqHpbuWMiBtAC5Nrnt8sJLuskII0TVJyKQd/klFg/aAH42rU32OtC9p8J8L7dddAXAn210nJ1xrz7N9iR1O3Mmt31J6dvmQsbcv2D+f3Lt9K5rRYENQrCmOB8ed9n6bcmt8nhDc2b35eYeNnfoUDDnFfvzRb+CLh8GfBf5MOyD6Mxuep/WBPg0jJbf6Gagf9OUAF4kZhIO1/OL1NY2qeIW4PD6cnXQRecuyiBoWoZhBKGoQjtrBKxQ1CUUb7sOx+PNG08KNX4+aiXWEdltHOGbi1lVeuXw8h905u9XLV3x5y1FMuOvjFit5HUVVwKVrOHUVp67iit87Nftx42lOTcXlsO8b5tcalms03e/WOWZQFtf8ezG3T+3NLW+sZe7aEib07cadJ/XlN++t56EzR+LUm3YbXVS8iIcWP0SGJ4N7Jt/D2vK1zHhjBm7NzRezvsChOZi7bS7DMoaR5EzqpL0muhoJmUII0TXtp30XuziHx+4ieH+jrojH3wtf/a0hdISr7Fss1DDPzm9h/uOtr1d1wP/tanj+xFH28u6UlgNp7yMgK74NdWUQrrav/+dM+kGDnliWRTBqUFEXjd8iVATjj4MRKuqiRGMGN00byKqiKub9Yhw3/fc7Pv+uhIn9unH3yf244931qIrC3e+tQlMVktw6fpeDJLfe6OaIv67jc+qoqmKfL1hX2rzq2GMc9Bxnb+CiZ+D92yBc2XIDPGkNIdMR7y4ajtqvtxQes4Y0LHvELXDUr/ct4O+pu+jn9x3w3UVbOsjw/opi3l9RnDjI4HFoicAXTgS0poGvyfPdglw4ajQLfE1CYKPnDa93XCWvtCZCTSiGrjb/vNSEYpTVRhiYncSW8mCLIa5JyNN2C4G7h7yWpmsqLoe22/qaTte19js3MBiJ8aeZg0jxeHn6okObTPvTTDcx02TFzqX8ffnfyfHlcNtht6GrOguLF5LkSMIwDfqk9OGeSfcwOns0jvj1PyfkTWi3bRbty4waqF2lF4sQQoh2J5VMOrCSeebz9vl0ocr4rcK+zEBK/ILc2xfDyjcbTd/tpuoNI3AC/CFnz5cSOPFBGHWB/fjz+2C2fSkYCwXcAQxngKgjQET3U+ntyecDbqOiLkplXZjBW16g1PBQEvVQHHVRFHaxLeik1PBQgxurlcEr9qWrXHVM45y/f8Xq4mq8hMhQKsigggylkgylgmeNYzDj63/CcR/D1PWkKZXomM3eb27uRSzpezl+l86gkvc5dPHNAJiaC8ObCf5MtEAOalKWHSAn3dgQFKuL7ctb6O1whtx+3F3UMO2DCcFI/BY1Gp5HYwQjZvx5LH5vUheNEYoYqArcNG0gY//40R6reJPu/piSms6r4gG4HSpuh4Zb13A5VNy6htthhzP79fhjPT5f/fwOzQ5tTabFl9U1fC6NfplJlNXVkh1oXnErqqomzetrVsk7EI15dgwxs+FzoKs6C85ZAMD8HfO5+IOLyfBkMPu02RiWwWtrX2Ns9ljyk/I7dbAe0basmIllWCiagtLGn3upZAohRNcklcy2tlsVyzrpYZQ3rmpaxfJ1azjHrrHcEfZtH1nnvUG4poK66lJC1WVEasqJ1VZghiogVMn8tS6WrV9KRTDK0Ts3MB0nLiIoWBCqRA9VogMeYJtZxK9W2gHWTx3fuB9u/oYO+2ZaCtfpt/KtbywpXgczIm8zNLoUwxVA86aQofRHmfcEfHYP7m0LuXLa/bj+cw6sm4MbcI08jxfDl+PxluAyg83eZp5rAhvDfqKGRapSTaZSDtjvW0oSJVYKu6xkdpLKhxsDvL9+DQABUslQ7mGnlUo1HqhVIF74deoqAbdO0oJP8bv0RKU0yV3UrIpaP72+otqsqroP2mvQF9O0q3918QAYisYfNw6C8edNprUYGFteRyTWPMzvq/5ZSZRUh1sMmABVQbuKl+5zNQmZ9QHOpTcEv8aBr+H1poGv/vXdA59r92CoN4RAl8Ou6rVniAlGYmQHkloNWXWR2A8eZdSyLCJmhKgRxefwoSgKRbVFhI0w2b5sXJqL9RXrKQ+X0zPQk26ebqwpX8PGyo30DPSkf1p/1lWsY/6O+eT6czki/wh21OzgP9/9B7/Dz4VDLiQYC3LXV3cRNaP8dvxv0VSNX839FaXBUn419lfkB/L5w5d/YPHOxVw98momdZ/EY0se4+U1L3PWgLP42dCfARAzY8SsRp+FRh+t4ZnDuWHUDRyWe1hi35xWuJeRk8V+xzJMsKDkH8vJuGTo3hcQQghxQJCQ2dYcXqyJN6AA4XHX8cjnW7ny1Gdxzbvffr2FKpZlWdRFDCqCUcprI1Tu1gW1oi5+H2z6uLIuSsQwgaT4rWfTFW8G2ArAh0zjZqbhIkISQQJKLWlakBxXmCxnGIfLwzFpWaR4HGQ7g6zZehx+qwaPWYMrVoMjWoUeqUYxQqiKxYPnTWzopvrq07Dsc6iOv+/rO+zzGeOjq7oeGWa/3udIYodfh/7SOaSEtjTZZ3Z3VbvL6ofTJmAl5RCOmQQ3ZbI1EqNSS6NCSaY6YlEVilETilEditEjHOXM+OPqcIzqUBQlFMMXsh/XRgwAIjGTkprIj6qeKQp2AHU16tLbKJgG4oF02pBs/rt0Ow/NXptYtr676NVH9WX68DzmrNrZJNyF4oGvroWAGIoY1MWnh39EAPwh7fU4NDzx4OZxanid8ccO+7HHoeF2NjxP8TrISHIR8OitVjIzk9z86+JDcWkdE/g6gzveLbC1kHX7vFs4vf/pjMkew0urX+KdDe8wrdc0zhhwBh9u+pCHFj3EqKxR3DH+Dr4p+YZLPriELF8Wr538GrXRWsa9YP/ufX3O17g0F+e8cw7FdcW8eMKLDEofxN0L7uZ/2//HHyb8gZP6nMR/1/6XZ759hguHXEj/tP4s27WMO7+6k0ndJ3FE/hHsCu7ib8v+Rp4/jwuHXIhlWbzynT168P8d9n9oqsaCogXsqN1BZaSSfPLZWrOV1eWrKQ/ZB4HqonWUBEuoijQaDbkVlmXh0lxcMOSCttvpotMYVWGiRXWofgfOXD+hNeVUzdmMUR4m6YjuAEQ2V1O7eCe+EZltXs0UQgjR9UjIbGPBSIx3lpcyfujl3PT8N3z+XQlLtlRw98mX88WyEvpmJvHwnLVUxgNkeV2UymCEqPHDey07NIUUr5NUr4MUj5Nkr4MUj4NUn5Nkj4OU+OupXoc9zeskxePA69T28OX+pZZfjobsc0ndyQ2vjTwP8g9t0rXXXDsbjr8P9eGGymz0hIdQFM2ef9KNDcHS5W/2Ngr2F3V33zGkAt1/4L4xTIuaePi07+3H1fXBNBSjJtz0eUvzxkwLyyIxD5WhFt8vzefkogkFPP3FxhanP/3FRi6d3KfVyzd8H26Hitepx0OgaodAhx4Pffa0+kDocTZ9ngiLzkZhsf55/P6Hhr9gJMaF4wtaHPjpwvEFxEyTzCT3j2p7VxI1oxTVFJEfyKc6Us01H1/DxsqNzDm99cvSfLTpI8bnjmdM9hi21mxlYfFCBqcPBiAYC7KxaiN5/jwAFEWhOlqNN2Kfx1t/fiJA1Iji0lz4HX5qHbXUn/2Q7cumV6AXHt0+qJWflM/IzJHk+ex1dk/qzrE9j2Vg+kAAMjwZzBowi1R3KgBOzclVI67CoTpQFTsQXD/6eiJGJLFdVwy/gnMHnkvf1L4AnDPoHE7scyLpnvQmbc3yZnHX+D9x8xe/pDRYmmiT2D+YwRix8hBGRRijPESsIoxRESZWHsJ/eB6+EZnUzC+ievZmfIdm4zylH1bMJLKxCi3ZiXdEJsX3LwSg+qNN+EZkdnKLhBBCdAQ5J5O2PacjEjMZ/YcPf9Cokk5NtQNho7CYGg+F9WExNR4Q68NiqteBx7GnsNhJDqDRVS3LIhwzqQpFExXU+nDauKpaHYric+mcMSaf8X9qPWDM++WR/HPeRiqD0YYQGA92HuduIbDFCqKOS1f3uetuZ9gvLmHzA4RiIVaVraIiXMER+UewuWozM/47A4fm4ItZX6CgMOHfE6iL1rH4vMWMeGZEk0qmrugsPm8xL6x8gUNzDqVPSh9Wl61mY9VGegV60T+tPyXBEjZVbSLVlUrvlN6EjTA7anbg0lzk+HOwLIvaaC0OzYFTdXa93/1Gxjw7hltG/ZKTC07ivxve4M6Ff0qckyk6n2VZmDXRRiEyTKwiRMrxBSgOjeIHFhItav28/6Qj8kme2ou6JTup+ngLnsHpJB/bC6M6Qnh9Jc6eSYTWlFPxakOvjpSZ/dq0minnZAohRNcklcw2Vh2K7vF8tOpQjN+dPARFgRRPvKoYD5ZdMiz+EAfY6KqKoiTO9cvchysnRGLmHruLpvtd/HLawHbY0q7D5dD4+eTeXDGlL9WhKEluBzHT3O8C5pbqLXyw8QPcupuzB57NqrJVnPvuuWR4Mjgi/why/DkAKCjsqttFli+LP038ExneDMA+z7DxeYi6av/JnTVwVuK1/mn96Z/WP/G8m6cb3TwN52y7NBe9knslniuKgt/ZvPrf1USMCAvOWYAVM9n1t2XMuGQGpwycScSI4NTaYbAt0SIzGCO6oxYUcBUkEy0JUvH6WrsaWRGCWPPjzP7xuTgyvCgeu2quenW0VDdaigs9ce/CkWN/Dr3DM/EOb6hQaklOvMMysGIm1bM3N1m3VDOFEOLgICGzjSW5HXsMGKleJz8ZmtMJW9aBHF57FFVoGE31zOfjAbPrj676Yxmmudfuoj900Jf9Sf21UNP9LoAu22bTMgkbYTy6h3nb5/Gvb/9FYWoh1466ls1Vm3lg0QP0CvTi7IFnU5haSKY3k/6p/QkbYVyai7dPeZtMb2aiW+nE7hOBhpC1uwMpZFmmhVkXxayJYoZiuHolY1kWVR9swqyNoh9fQN2yXfb5eF8XoSY5CS7ZheLSUN26fe/ScOYn4SpIxqiOECsNorh0VJeG6tZQXBpKO15uZX9mRU1iFaFEBdIob+jK6uqTQvIxPQmtraDsuZU485PIvGI4iqoQXlvRsBLFDoVao/CoOO2DQemzBiR+Rt9722ImdUt2YlRH7YuyxhnVUeqW7sQ7TM7NFEKIA5mEzDYmASPO4YlXLD0tPz+AeZw6lx/RB+CA6y66v4saUdZVriPgDJDrz+XZb5/l0SWPMqPfDG4acxPVkWo+3/Y5ZaEyAAamD2Rqr6kMSh+EZVl4HV5mnza7yTqzfdktvldrQbIrB0zLsrAiBmZNFKPGDo9ashNn9yTCm6qo+WI7Zk0kMc2si0J9IUxXyPvd4SiKQs0X21HdGikn9klUsqo/3kLWdaOofGMdRmXT0wX8E/NwFSQTWlNO+ctrmm+YrqK6NVSvTvb1owEofWEVKJDyk95oSU5qFxZjhWIobjugNgmybg3Vo6N04u/eD7lOpBmKJUKjfR/Gd2g2jm4eyl5cTd3ina0uWx8M9TQ3WrobLdU+2KMlu0g9tRAt1YWe4kJLdrUa9rTAD/+sWqaFb3Q2vtEt/36YEYMDoN+OEEKIVkjIbGMSMBrZvUvsftRF9sc6ULqL7u9WlK5gyc4ljM0eS9/Uvvzuy9/x2trXuGzYZVw+/HJ8Dh810Rq+K7cPCo3IHMGvxv6KQemDAEhzp3HP5Hs6swk/mhUzMWujqAH7/M26ZbswKsJ4R2ai+Z1UvLOB8PqKRLBktxGMfYdm4+yehFkTJbh0V4vvoXp1VL8DK2qiODX8E/JwF6ZSu7g4ESiNygh1S3eRft4gQqvLscIGZtjACsVwdre7XSq6it7NgxmKYYUNrGh8W2ImZo0Jpp1oLcsiuGwXWJByfG8Aaj7fRrSottX9kHREd5KnFlC7eCdV725AcWuoLj1+rzVUT30OAkf1AKBu6S4Up4q7byqKQ8WoDIOm2OH1e1ThrJgJpn3feDkrZhLdUYtZF8XdPw0rZlL63MpEoLRCzXvEOLv7cXTzoHrsf9+KU0VLcaOnutBSXGipbvQUF3qm/ffWmecn58YxieUVTcE3Omuft/2HUp17/lu3t+lCCCH2bxIy24EEDAH7T3fRA4FlWSiKwgurXmBB0QJ+PvTn9E/rzz+W/4MPN33IL0b/gr6pfemf1p8kZ1Li2pVH5B/BKye9QkFyAQAZ3gzOHHBmm2/fD6litcYyLcxgDLPW7obo6OYhVhqkdtFOzNpoQ6WxNopRHU0EldzfjENx6VS+vxGjNISzRxKa34lRGiS6tabJeyhOFdXvRPM50FLsz68j10fyCb3R/A5Un8Oe7negevVm3VmTj+mJFTMpe35lk9er52wm+8YxOPNaPrnZOywD77CMhrYaph1GQwZWpFHotCB1Rj/McCwRttwDUtEzPfa8YSMRVM2wgRWOocQre2ZNFKMqAq1caUX12yHTMi3KXlgFQM5tY9EcTnb9YzmxnfFr+2qKHU4bVU59h2bjG5lFeH0lwVWlqC4dNcmJd3gGJf9YTreLD6Hs36tQgLQzB2BUhNn56BIUh0rub8ej6Crh9ZVYYaNhe7x60/CYZo/MnHRkPklH9bD3/4FwLr8QQogDioTMdiIBQ4i2Z1omW6q30COpB4qicP0n17OoeBFPHvckvVN688mWT/hi+xcclnMY/dP6MzZ7LFEjSq4/F4DT+5/OWQPOSnwpT3WnJi7b0V5aq2I1mScekiPbazAqwzi7J9ldQBcUEVpnVxnNmihGbcQOl/Gs5R6cTrdzB2FUR5oNsNKECmZtDNWl4xmQhlEbRXHZf6P8k7rjHZ2F5nfGw6OjxSqTnuomaULePre5Lc7HUzQVxauieh1NX1cVfIc27YaZPLWg9e2xrES3Xu/ITFwFgXj4bKim1j9XNCXRBlffFMxQDNUd/1fZuMhrWJh1MaiLUR8JPQPTAIhsqabms20ApJzch7qFxUQ2V1O3sBhXzwDVn9jXCdZSXGgBJ1qKCytiorg0Uk/pi+LS45VJd6vnQ2r+rtvtWgghhJBLmCBDoAvRFcXMGKvLV7OxciM/6f0TomaUyS9OpjpSzYenfki2L5tz3jmHpbuW8qeJf+InvX/Cuxvepai2iEndJ9EnpU9nNwEgMbpqt4sPoeaL7cRKgnaVscauOpo1UbKuG4We5mbno0uIbKkm/dyBeAZ3o/zV76j9qqjF9SpuHXdhCulnDcSoClM1e3NDddHvQPM57Xu/A8Wto3TgJW/MiLHH7pB7m96VWWb8vNWQXSG1Q6qBGY7hyPLhyPQSWldBaHUZKAqBI3tQ/OevMSojaMlOsm4YTWR7De5eyXt/M7FX8v9bCCG6JqlkCiG6hPJQOW+tf4vyUDlXj7ya2mgtZ75ld12d2H0iAWeALG8WESPC1uqtZPuyuW7UdThUB/1S+wEwrWBaZzYBoypMeFMVkU3VKLpK4Oge1C5qqGKpLo26r4ubL1cTQU9zo2d57apbvMrnGdINvZsnHhbtSmN9d9XGlUAt4CJ1Rr8Oa+feHMjn4ymqYneRdeuAq8V53H1ScPdJwYqZ1C5qfl6qXMJDCCHEgU5CphCizbV2mY6wEcYwDbwOL9+Vf8djSx7DoTq4e/LdhGIh7l5wN7qic+mwS0l2JTMwbSABV4DKcCUBZ4C/HvNX0txpietNjsoa1dFNS7AMi2hRLZHNVfFgWYVRHk5M13N9BI7u0TC66idbyLphNJZhoThUOzTGK41ash1W0k4tbPIe7sJU3IXt251XtC+5TqQQQoiDkYRMIUSbsSwLwzJwak7GPDsmMcAOgK7qLDhnAVd8cgWPHvUoCgofbf4Ir+7FtEyyfdkcX3A8vQK9EiH1pRNfarL+TG/nfTk3QzEim6pQXBquXsnULthBxevrms6kgCPbh7NnAN+4nBarWP7DcuT6gAcBuU6kEEKIg5mETCFEM5ZlURWpojJcSX5SPoqi8OGmD9lVt4upBVNJc6fxxLInWLprKecOOpexOWO5f+H9PPPtM/xsyM+4fMTlxMwYMavRJRjig6asLV8LQK/kXvxi9C8YkDYAy7JQVZW7Jt3VCa1tzrIsYqUhIpuq0FNduHqnUDu/iMp3N+AZnI6rVzLOHgEUl4azZwBXjyScPQM4eyShxgfUsWImpU9+02S9UsU6eMh1IoUQQhzMJGQKcQCrH7V0V90utlRvIcWdQu/k3qwpX8P7G98ny5vF6f1PZ33Fem6deyteh5cnj3uSYCzIhH9PAGD+WfPxOrz8+es/s7VmK4PSB5HmTmN5yXI+3fopk7pPYmzOWHRVJ2bGqIxU7nGb/jv9v4Bd2Tx/8Pntvg/2hRU1iWyrJrKpivAm+96sjQLgHZGJq3cKzp5J6OlutFT7EhKObB+5t49rcUAdqWKJA/m8VCGEEGJvJGQK0Q5aOyextdf3xLIsaqO11ERryPZlY1kWH2z6gMpwJSf1OQm37uahRQ+xvnI9lw+/nMLUQu744g7e2fAON4y6gTMGnMFLa17i8aWPc0b/M7jtsNvYWLmRvy37GyMzR3J6/9NRFIUVpStIctjXL/ToHhyqA4fqoCZag9fhZXzueMrD5Xh0DwCnFp7KpO6TGJk1EoBzBp7DaYWnkeza86iZbt39vdrfHoyqCIquoHodVLy7gZq528DYbaBtXcGZl4QjxweAq1cy2Y0var+H0VqliiWEEEKIg5mEzHbQlgFD7J/2dE5icW0xRXVFZHgyyPXnsnzXcuZum0tBcgFTC6ayZOcS7v36XnJ9udw9+W62VG/hJ6/9BK/uZf7Z81EUhdvm3kbICHF43uHk+fP4cseXLC9ZzvS+0ylMLcTCIhgLJqqKWd4seiT1IOC0h/jvndybWQNmUZBsX1swx5fDI0c+kgiIiqIw/+z5ONSG6xP+37j/a9LGSd0nNXm++/UmdVVvcl3B+sF6OpplWESLa+NVyoYBelKm98V/WA6aVwfDQvU7cPUM2N1eewZw5vl/cLVRqlhCCCGEOJhJyGwHewoYYv9Q3820NlrLrrpdODUnuf5cykPlLChagEN1MKXHFOqidTz5zZOEYiFuGH1DIgD+fsLvWz0n8a/L/srLa17miuFXcOmwS1lespzHlj7GMT2PYWrBVKJmlKW7llIZtgNiffAzLIOoGcWhOjg873BMy0SJ18POGXgO1ZFq+qb0BeCyYZdx8SEXk+5OB+yq46mFpyY2pW9qX24de2viuVt3Mzl/cpN90Dhgfl8RI9Li570jD7RUf76V0OpyIpursSJG04kKGBX2SLDekVl4hnRDS3OjKFJfFEIIIYT4sSRktpPWAsbT3zzN/KL5zOw3k6N7Hs3cbXOZs3kOIzJHcGKfE9lUtYkPNn5Ati+bE/ucSF20jtmbZ+PRPRzd82gAFu9cjKZoDEgbgFNzUhIswbIsUlwpODRHIiB1po6o5lqWRcgIYVomPoePumgdayvWYmExLGMYESPCm+vepC5Wx1kDzkJTNR5a9BC7gru4bNhl5PpzuXvB3SwqXsTlwy9nUvdJ3L/wfp799lnOH3w+V4+8mnc2vMNv5/2WKflTeOjIh9hYtZEbPr2B/KR8pvSYgmmZ/HXZXwG4auRVuDQXC4r2fDAhy5NFnj8Pt2Z3Gx2QNoDTCk9jSLchABSmFvLAlAcSATHgDLDg7AVNupk+MOWBJus8vvfxTZ5n+1ruptlRWvsZt3XAtCy7i6uiKFS8tZ7Qd+WkzxqAI9tHeEMV4bUV9nSXhrNHUkOlMj8pfp1D0JKkd4EQQgghRFuSkNnBVpevZu62uYzLGQfAytKVvLzmZQzL4MQ+J7KuYh0PLX6IoRlDObHPiZQES7h17q34HL5EyLz4/YuJmBE+PPVDsn3ZXP7R5awsW8lfjv4LE/ImcOvcW3lv43v8YvQvOHvg2fx71b955ttnmNprKlePvJrFOxfzyOJHKEwt5OZDb6Y0WMqfF/6ZJGcSvzz0lwA8vvRxNEVj1oBZ+J1+5myeQ220lsNyDiPDm8F35d9RGa6kR6AHmd5MKsOV1ERrSHImEXAG9lrNNUyDeTvmURet48geR6KrOi+tfoldwV3M7DeTbF82T33zFEt3LeWM/mcwLncc/1zxT15c/SIn9zmZnw/7Oa+vfZ1ff/FrJuZN5LGjH2N95XrOfudscnw5fHDqBxiWwR3z7gDglH6n4FN9vLPhHbbVbGNmv5nk+nPZXLWZFaUr2FW3CwBVUYmYEYKxIAB+h58kRxIuzb6OYaorlZGZI8nyZQH2uYtn9D8Dr+5NBJ7rRl2XaHOWN4u7xv+Jm7/4JaXBUgB+Pvzn/Hz4zxPzjMwamTivEezK5VE9jko8VxSlS5zH2BU0DNBTnej6mnn5MPR0D9GiWmLFdYQ3VuHI9uE7NBt3/1RcPQPomd49nkMphBBCCCHajoTMDnZa4WmMzRnLkHS7ajUqaxRXDL+C/qn9AbsCdUq/U8jz5wF2l8VxOeMSFSDLsshLyiNiRBLBB0BBwana80SMCDEzluhKWR4qZ0v1lkT3y111u/iq6KtEAKyMVPLGujdIdiXzy0N/iWVZ/GXpXzAtkxn9ZuDHz8OLH2ZtxVqeOPYJMrwZPLHsCd7d+C43j7mZcwadwwurXuDRJY8ys99M7hh/B9B6Ndd+aHLZR5cBMPfMuSS7kvnXt/9iY9VGxmaPJduXzdJdS5m9eTbjcsYxLncc1ZFqtlRvYVfQDoRehxegSSDM8+eR5bUDoFtzc0T3I/DonkQAPHfQuQRjwUSl7+JDLub0/qdTmFoIwPmDzuf0wtMJuOxzF6cVTGNawbTEdvdK7sU/p/0z8VxTNW477LYmP+OpBVMBO1RfPuQyhqcP4/Ihl3Hnwj+19rEQrbAMk9DKMsIbq4hsriKyrabZAD3hzdXo6R6SJnXHPy4HZy+7e7FnQFpnbLIQQgghxEFPQmY7aW3Qk92rVrs/H5Q+iN+M/03ieY4/h78d+7fEc0VReGP6G03e66UTX0qEKIA7xt/BjWNuxO/wA3YVb1zuuMTALEMzhnL3pLsTg8CkuFK4btR1aIo9GImFxWmFpxE1o3h1O8iNyBxBhieDVJe9jnRPOr0CvRLrVFBwa+7EyKN741AdDEkfglNzYlj2+XLH9TqOinAFaR47HMzsN5PxueMZlTUKgBn9ZnB43uGJEDklfwpfnvVlottpr+RevDfzvSb76uGjHm7yvmcPPLvJ8+GZw5s8T3GnkELKPrVhT+rPSbRiJrv+towZl8zglIEzD8rBn8yogerY+0A3lmkRLbIH6IkW1ZIyvS+gUPbSmibnVKp+h31tykYD9AC4C1NbWbMQQgghhOhIitU4nRykqqqqSE5OprKykkAg8KPXJ6PL2kY8M6JJJVNXdBaft7gTt6j9RXfVES2qI1Zci6O7H6M8TMV/15EyvQ+KS8OKmPjH5hD8tpTaBUUoDhVFV+17h5Z4rvp0/IflYlkWwWUlKA4Vd2Eqiq4SLa4FaJg/vgya0unn4u7OiplYhoWiKc1GajVDMSKbG7q97j5AT/ZNY9DT3JS/9h0Azl7JuHokyQA9QoiEtv7/LYQQom1IJbMddNSgJ11dV7mERXuxDIuauduIFteSOqMvikOj5MlvMMrDaMlOsiaMovi1hQBUf7yFrOtGUbt4JwCxkiChlWWtrltLduI/LBdiFmUvrAIg945xKLpKyT+/xSgLNV9IAcWhEjimF0kT86hdWEzN3G27BdmGMKv6HSQf2yvRDsWh4js0G0VXCX1XDqbVLPwm1uHSULR9u7xHyT+Wk3HJUGJlIWLlIdx9UojurKP4/oWw2yGuxgP0KLodJFNn9Nun9xFCCCGEEF3DgfWtX3QZXeESFm3BrIsSLaojWlxLtKiWaHEdRlmI7F8eCipUf7oFsy6G//A8nHl+nD0CxHxBko/tRd2SXRiVEQCMygh1y3bhHdoNsLt2Km4NK2o23GImxB8r7njXZcvC1TvZfs1hhzrVo2N59cRyCRZYEZP65GZURYjuqG21bVqa2w6ZMYPKdzcA4Btjd0Uu/893GJXhVpdNnlZA0uTuVM/dRtXszU0qqopTQ9FV/BNyMasjRDZXU7uoGAyLqjmbybl1LHq6B8WhoSY5cPVouDalI0sG6BFCCCGE2N9JyBTtYn+r5poRAzMYQ092ES2qpeLt9USL6zCrIi3Ob5SH0NM9+MfngqKg+uxfpfRZAwC7m2j5K2uaLFM9ezO+kXaIc2T7cGT79rpdqlMj45KhTV7LumpE4rFlWRCzsKKG3TU1aqJ67G3xDsvAmee3pzUKsvWPFVf9eZIK3pGZdmCNVycd2V5Ur95kfnt5A0wSVUYrFMMKxrCCTbdbS3bi7pNiVyvjbc+6bhSh7yqwwgaqWyfnlkMT2yqEEEIIIQ4c8g1PHFQswyJWGrSrkvHKZKyollhZCFfvZDJ+NhQ0hfB3FYlltBRXPBR6cWT50LN9aCn2yL6Bo3s2f4+YSd2SnRjVUWhUlTOqo9Qt3Yl3WGaz8xN/KEVRwKEkqpyN6Wlu9LS9X/pEdWmknd6/yWvdLhzS6vyW0VA99Y/PxTM0Ix5CG8Ks1s1N3dLdKrnLS0g/a0Ci7RIwhRBCCCEOTPItTxywjKowke216GluHJleqj/bSuX7G5tdAiMxf7UdiPR0Dykz+trBMsuL6v5+vyaWaeEbnY1vdHaL082Iwf7cIbTxuZiq14HqdTSbx4qZlP7jmyavVX+0Cd+IzHbfPiGEEEII0bkkZIr9nlEbJVpUS6y4jmhRLd7RWbh6BKj6cDO1C4pIOjKf5GN72WHIsFCcKnqWHSDrg6Qj24fqt8OSoir4x+b84O1RnXu+XMfepu/vOrKSK4QQQgghuh4JmWK/U7uomOj22sRgPGZ1tMl0Pd2Dq0cAR54PfXNDJdIzKA3XjaPRUt0yuEw7OtAruUIIIYQQYs8kZIp2Z0YNVMe+V+8swyRWEmw0qqt9n3XlCFSPTvWnW4kV1zVZRktzJyqSzl72tdL8h+XalwGJa61rp2hbB3slVwghhBDiYCchU7QrK2aCad/v3kXSsizMuhiaz4FRFabinQ3EiuqI7qpr8bzJaHEtrl7JeIdnYNZEcWT70LPswXhUlwQXIYQQQgghugIJmaLdlfxjORk/G0poYyXELNx9UwhvqqLkyW/Qkl1kXz8KxakRXLIrsYzi1BqN5mrfO3LsS34EpvTorKYIIYQQQggh9kJCptgn9vUYTcyQgRk2sMIGZiiGFX/syPPjyPQSWlNOcGUpVtjAc0g3jMowkc3V1H5dBEDd4p24+w5HS3FhhQ2M8hCWYaK6dZJP7I2e6sYRv0SInDcphBBCCCHE/kdCZjv7vucjtjXLsMCyUHQVozpCrCyEFYrZQTFkYIZj8cBooDhVko/thRmKUfLUCqxwjMyrR6KoCkV3foVRFWn1fZJP6I0j00tkWzW183agJTtJOakPxfcvBKD6ky1kXT+K2C77XEot4CTrupHo3TyJS2IkHZ7X/jtECCGEEEII0a4kZLajPZ2PuMflLMu+qH19CAwZWKaFq2cAyzCpnV+EGY6RNKk7iqZS8eY6OzyGW6gyRk2Sjy8gaVJ36hbtpPLdDa2+r5bsJPnYXii6SmRTlb0tEQPFraM0GqxFcWmoLg3FraG6dBS3hhZwAuDqmUzSlHw8g9KoW7ILo9IOpkZlhLplJSQf39teh6LgyPJ9730qhBBCCCGE6NokZLazkn8sp9vFh1C3uBizOpoIf/Vh0DMkHe+wTGoXFlP1waZEZZHdxr1R/Q5ybzsMFIWKN9YB4Ds0B82nEvqunNjOYKvbYIZi9jqSHGjpbjsguvRGQVFDcetovvh1InWV9HMGori0RDjOuHQoikNFcWh77Mbq6p2Mq3cyVsyk9NmVTaZVf7QJ34jM770PhRBCCCGEEPsPCZntxIqZ1C4qJrK5mrqFxQBUvtO8iqinu2EYYFoYleGmE5X6qqGO6o8HQFXBOzwDdBUlnvWSpvTAihio7nh4dGsoTg3VrdvLu+0qpG9kFr6RWfu0/Z4h3Zo81/zO79X2uiU7Maqj0CiQGtVR6pbuxDss83tVdoUQQgghhBD7D8WyrObXijjIVFVVkZycTGVlJYFAoE3WacVMiu5ZgFEZQUt2knX9aKre34hlWQ2VRLeGI8+Pq0cAoyaCURFOhErFrdmVQ2X/G/zGjBh7vBbi3qYLIYQQ+6I9/n8LIYT48aSS2Q7qq5hNz0fcRfLxBa1W8DS/83tVC7uyvQVICZhCCCGEEEIcuKTPYjupnr256fOPNnXSlgghhBBCCCFEx5GQ2caanY8Yv9Wfj2jFzM7eRCE6jGlaWJaFaR68vfJlHwghhBDiYCPdZduYZVr4RmfjG53d4nQzYrD/nWX5w5mmhaKAZYG6h1FpxYHHNC2ioRhznlnFkecNwOHWD7rPgOwDAfJ3UAghxMFHQmYbU51a4ovlq/ctomJHHSk5Xk65YaT9BfMgOh9RvmAfvF8u63/2r9yzkPIddZQX1zLzxlFd/jNgWRaWZR8savrYnu7y6FiWRbA6imVZeJOcKKpCTXkII2ZimQ3rcLg1HE6NV+/dv/aBaFvyd1AIIcTBSEaXpW1Hp9v9y3W91BwvM64fyeZvS9mxrgpFAUVRUFT7PqsgQL/RWZQX1bL6yyL8aW6GTMojVBvlm0+3gqI0WkZptryiKvQckk5Smpvt31VQVRIko2cS6bl+ynbUUrqtpun8CvH1NKxL1RTy+qcCsGNdJQCZPZLQHCplO2oxoiYo8bCktLwep1vH7XcQixoYUTOxH1JzvMy8cRS6S0ONz3+g2x++XNZ34zRjFkbMTNwaP0/J8uJ06+zaXE1NRZj0XB+Bbh52bqpi56bqRsuYGDGLbvl+cvum8NqfF7X4O7B+yU76jc7G6dH59IXVVJeFsEzAah7sLMvCMqHPyAyGH92Dzd+WMu+1dWT2SGLKuQOpKK7jnb8sw7Ls/U18/pbC4vGXDSWnTzIfPrmC9UtLmHBqXwZPzOOrN9fz9Tsb2dtfQk/AyUV3T8AyLR67/GMAfnrvRNx+B8/d/iUVxQ1tHTwpj0N/0ovXH1jcbB/MvHEU1aUh3nxkKbn9Ujju4iHUlIf49IU1ON0aDreO06Xh9Gg4XDoOt4bTrSempef6cHp0omEDVVPQuvjlgA7WAy3Q/P9B/c+/K/4taE/t+RmQ0WWFEKJrkkpmG1MUmPPMqiZfLAHKd9TxyXOrmXrJEOb8axVmrOk32oHjc+g3OouK4joWvreJrIIAQyblEa6LMv+N5tfXbMkJVw0jKc3NirnbWDO/mPEz+5Ke62fD0l18+fr6vS7vcGlc8uBkAP57/2KMmMl5fxxPUpqbj576ll2bq/e6joHjczjinAHEImaiglPf/lfuWcj0a0fw1dsbWTl3O6qmoGh2uFXV+E1TOer8geT1T+XL19exaUUpw4/uQf+x2az5qohv/7cDrX45tWFZez0qqqrgcGpMOL0fAPPfsNs9/Oh8XF4Hq77cQagmiqIq9nri76k2Wp+iKgS6uenWPYlQTZSyHbW4vDrpeX6MqEnFzjp7/vi8mqbG19N0e2Jho8VKXixiEK6LNQ1zRjykRS0Mww5tiqLQe3gGlmWx/JNtGDGTQybnoTs1lny0mZrycDzY2eHOMEyMqIlpNATEgmEZjDimBxuXl/D5i2vI7BXguIuHULq9hpfv/BojZsJewtX060eQV5jK1+9uZP3iXUyeVciQyd3ZsKyEr9/e2GReVVe49KEjeO9v3+zxdyBUGwVg2+pyyouazteSbvl+AMJ1MUq21OB023+6jJi5T8sDmPHzoY2YSSxsYBp2wy3Ya8C0Z4zPFP+OrKhK4jxL3anaB1AU0Bwqk88sbHUfzHlmFVN/bu+DcF0MgGB1lI3LSvapHTNuGEluvxQ+eupb1i/ZxeSz+jNkUh5LZ29h5Rc7GoKqW0sEVIdbwxkPrJ4kB31GZGJZFiVbanC4NAIZHlRVwbKsNj0A1NUPtNS3NxoxCNfG0HQFT5KTUG2U8qI6jKhh/25FTWIxw/79jNm/Z0bMJBY1GXZUPi6PztfvbqRyV5DhR+WTnudn07elZOQn8Xqjgy2Jv4PXj2Tdwp1sW1NBcqaHcdP72H/r39yA7lAZf0pfAJZ8tBnLtH+vNF1NHFRocu9QScn0kpTmJlgdoa46gtvnwJfswoia9sEI3f47Vf83qyN19c+AEEKI9iEhs42Z0RhHnjeA8uLaZhWMI87pz8ZF2+lT+RXuoUNxFhZiWVD98Sf4Fy1m+5rn8M68iKFTuuN1xih5/HHCioc+2emgaaBoWJqKnpUNKJjhCEYwCIqKpep4k+xLoKTn+ugxOI3kbh4A/Klu8gpTmlSG7PtG1SILHM6Gikggw4MZM1E1+8uAx+/Al+xsMr+1W9UI00JzaigKfPyvloP2py+sYeolQ1j5xXZiUROiLezD+Jf/qtIQJVtqCNXYM1WVhNi2unyvPwOnuyFkLnp/E6ZhMXhiHi4vLPloC6Vba/a6joGH53DkuQPZvraCdx9fTlZBgFNvHk11WYh//+6rPS7bUhWr/svlzBtHsX1tBe88tnyv2+Dy6fQengHA5y+tAQsKD81Cd2qs/GIHZdtr97qO1BwfYAerqpIQvmQXYFcTjGgLg1ApoOkqWvzLq6o1XKs1JctLZq8A7vildtJyfPQenpH4AqzFv/iuW7yTI87p3+rvwLbvyskqSAbg0BN7EwnF4tVt7Ip9otre8DjQzQ1Abr8UTrxqGC6fA4BANw8zbhgRr/Q3rqzvVulXFJLS7XVMPKOQcTP64vHb6xhxTA+GTMrba6W/fpg0RVG44vEjm+y2M351aJPnpmm1+nfgyPMGEA0bnHrT6EQV0pfi4oiz+xMJGURDMSJhg2j945BBJBQjGjaIhAxcXvvPdiRkB1SHy+6CX10aonTb3j/bSWlu+ozIJBY1eemPCwD42QOTcLp1nvv1lwRronZAdWk4Pbp936iS6nBrdO+fSv7ANKpKgpRsqSEp3U1GjyRiUYNgdRSnR0d3qq0eaKnPsYqiEKqNEg0buP0OHE6NqpIgtRVhYo3CnBG1A50ZD3ZGzMTtczB4Yh6hmihf/ncdAEecPQCAd/6yjEgolljODopGPCyaieB42Mm9GXlcT5Z/spV5r66j/2HZHH3BIIrWV/L2o8v2ui8B+o/NxuXR2bishOINVfQenkF6np8eA9N4768tH2j4NH6wZe5/vqNbnh+m9yFcF2P5x1ubhMz5b6wnFtn7YHHjZvRh5HE9WTWviC9eXUv/sdkcfeEgtq4u561HljaZV1WV5qFVV5l+3QiS0tzMfmYllcV1jDulLzl9klk6Zws7vqtAjf+ON7nX65+r+NNcDDgsh0goxtqFO9EdKn1HZ+2X3eaFEEL8eBIy25jmdLDrvrs45eorefWh5YkuUqdcfQgVD99PwS03E1r8LFlH/4K0k6cBsOo3p2EFg1QCvc8/n4lnFFK3aDGbbnkQgJ67vUf/ZUtRnU4qXn+dHb+8BQDPqFFkXPMsAFmzH8Pz5ltE/uFitcuF6nQyxOUi8JOfkHndtQAU/f4PRLdsQXG5SLvwArwjRmBGIhTffQ+Ky8mxWS4Ul5vw2xuIulxMO/dI9NRUjJoaQt+sQHE5Ub0+3P0LATCDQaxYDNXlwrL2/AU7HIpx7u/GY5p21c0yLUwjfjMtUrK8AIya2pMBh2UnnhcM70Ygw52Yt8lyhoVpmlimhao1hOVDpnTHNCycbvuLeK9D0knP9dkjfhoWRmI9pt1tNL6u5Aw7oDucGilZ3kRAAXD7HQ3vbTZsC9gVh32pYuluFcWq/4IXD2nxL231j50e+9dTURT6jc5CUUGLt23g+ByC1RFUTW1xHfWv17cjr18qp9w4KhFQAhkezv3DuEbL2OvYU1fmcdP7NHneb3QW/UZntTivaVrMvHFUi90Eu/dPS8zXd1Rmi8u3xpfsSgRlsANWbr/U772OxuwA1bZ/ClVVweHWW90HqqqQ0SMpMb834GTwxLzv9R4nXDWMaMhAd9ifiSFH5NFjSBrReCi1A6tBNNzwOBKK4Y6H61jEwJfsJBoxccTPFQ/XxYgE7dve2pc/MI3N35bx6fOrKRjWjeMvG8quTdW8eu+iPR5oqe/NMPzofFIyvbz1yFKKN1Qx7dJD6D08g4XvbuTb/+3Ya/vTu/sZPDEPI2ay4vPtqKqSCJnbv6tIVIn3xIhXtzVdbRJ6XB6dQIYH3dHw+6HFH+uO+OP65/GDc4Mn5lIwrBup8b9XVbuCTDmn5b+DU84ZwI61FUw4tR/u+AETp0dn1LSeTX7/+o/NToRqM95bob5bumk03HsD9oEfVVdw+x04vQ2V/t2ZpoUZsZqF1/q3LdlSTcmWGqLxgxg7N1axbvGuve7LrIIAAw7LIVgd5eN/rWLokd3pOSS9yakjjQ+2SdAUQogDm4TMNmaGw2TfcnPiS3bjLkLZt9yMUVtL/mOP4uzdO7FM1s03YQZDWOEwWrduAGipKSSfOhMrHMEKh7HCYcxIGCscQXHYX0oUTUfPyMCMRNCSGr6wWuGIfW5aKIQVClH/VcKoqkzMU/f114RXrQIgcOIJ9rbX1lL25JMttqvgv/9FT00lsnYtmy+4wN7G9HQK/zcXgLKnn2bXgw+BqtJ39kc4srJb/YJt7NpJ3Zw5pM2aBcDGM2dhVFXFq1gKtfYJn2TedBPpEw7HqKllw8xTQVFwKAo9nnoKze+j9ssv2fWXhxNVrHjJCS05AMc9DMAh7jVUvv46RbMVfGPHcthPfwrAzgceILx2bfwLnQKqCopCYOpxBKZOBaDod79Hra5iiqLQ7ejLAPBRwzT3+yh2ycu+qfY6ul17PYrHQ7QutMeQbdTWMT3v60T3S3f/QpJPPhmA8hdfIrJpE1gQmHis/fO0LIaVvgNA5WPvUAnk1K/zzDNw9uhBrKyM0r//I/65UMm84Qb757xoEcX/ng3YhbgoUAzo6emk//QiAKpnz6Zy4SIAvKNHkXSkXaUr/cc/iJWWNfssJB19NN6RI+z9eO+9iYCdfvFP0dPSMINBVI8nEbJ27yZnhsOEvvmGqrffwbJMXL37kHbuOXb7X3iB4IoVED+/EtMELLzjxpEyfXriPSPbtoEF6T+9CM8hh2BUVrL91l81LGNZWFhgWuT89jc4cnIIrV5D8Z13gmWhpabS/YH7Aaj4z3+oePW1huXsMj3uwYPIueMO+z3vu4+azz4H0yT1vHNJPe00ADaccQZmRaX9Xhb2OhSFgtdeRfP77X3wi1HM+dcqjjy3YR8YNTVsnHWW3fNW01BUFVQVLSWFHn9/wv5Zv/kmFa++iqKoeMcdRref/QyAXQ89RHjtOtBU+3MYXz7pmKPpcfTR9vb++X7M2lpQVdLOPw9n9+7ESkspe+ZfKFGVXQ/PBk3lhAINNBUrNBrF62XmT/Oo+Hw+UTQsbwqOoSOIhAxq124itLOMqKkSMxQC5Wup+nAdak0q2b2TScvxEfxmBTWry9Ecez7QUt+boWyb3f1ed9gHOOo/R95kF8mZnqaBLh7y9HjVTXeoiQM/To/OoScWoOlqovvr5LP6g0UiDOr6buuJv15/IGfolO4MOzI/sZ05fVM493fjmn3292Tg+Nwmz5MzvXs82JJbmEpuYcMBErfPwWEnNz2QUx+a99WwI/ObtKP38Awue2yKHUwNa7eA2tC13jQsPPGeMBNO60e4Nka3/KR4u3LI7p3caN7dQm583fU/D01X6T08gwmn9Wu1klt/sE0IIcSBS0JmG1NdDd0RHW6dqZcMxkJJHLHVfD78kyY1WSb1zDObrcdVUEDu73+/x/dKPvEEkuMBsbHcP/4B87ZfYYYjWJF4QA2F0NMaKkgZ116DUVqKGQ7jHjgQAMXhIO2ii+xQGwljhsKJgKslxwdU0HScfftghSNoqQ1fkMxwOL4DVBw5OawePYbAjBmccvU1fPzieqac0Zuy+++h6rXX6P/1Aszqhm59kQ0bMCobAnBinTXxeWJRQitWNEyw4ufWlZURXLSo2XJao3ZGNm+idq4dhLXklMTrwa8XUvf1182WdfXtm3hc9cH7GLvs8+RSzjgTZ69eGJUVVP7nlWbLAWRcfRW60w9OD0V3tlzNLn/wz2TfcjNl//wnxOxKQdLUqYmQWf3+e9R+MQ8AZ6+eeIYNA2g1/PuPmIyzRw+MysqGeRyORMgMrVzZ4rLOvn0SIbP2y/mU/+tf9gQjlgiZFa++RmTdumbLOrrnJUJm6dMN7Ug9/TRIS0P1eFg9egxWLEbyzJlM/dWtFP3hj1S+8gqKrtP/6wWE166j/PnnAfAdfngiZNbO+5LqDz5o9p6qzw/xkFnz+VzCq1cDJD7/VjRKzezZLe4js9buVmzWVFP35ZcA6JkNFdTo9h0tfo5Ud0P1Orpte+I9jUbBO7ppM0ZFRdMFdR3N79/rPohs2JDYd/W09PTE48jmzdTNs7dX69bweu1XXxH8emGz7XXk55MUD5kVr76KUWJ/dgPHT7NDZkkppX/9a4v7KOXUU1G9XtStawne/1sAXIMGUnDuqwDsePdxKv79YpNltgGBqVOZGQ/rmy64kNiXXzJJVYnWftXqgZYp5w2gblc5zi1rIP8wps1MZ+Npl2EsdbLW42XsB+8z9qTeVH34IeXPPmf3mnDZPSsUlxNHXh4ZP73c3hdffEFo5Sr6uFy4Bw9CUex+H3lswTJiKJoLVXGh6C4Upws9NRXVZ3chb3z+aXsNRNa4ot1Z5ySqqoLq1Pb5n31eYdOeAd0HpNF9QForc4NlmhCL2feAP9XFsef0JlZVzZHntn6wzbIaqqdCCCEOPAdMyHz00Ue55557KCoqYtiwYTz88MMceuihe1+wHamqwppxh1M474uOfV+fL/FFqjVJRxzR7DXN7yfrphv3uJznkCH0eeutZq9nXHMN3S6/PBFo+39tn+sVq65m6iWDMWrryPnVreT86laM2lqSTz4psWz3x/+CFY3GR2CJV5NME3f//nZ7vF7y//p4osJU/+XfM3IkeQ892Gy5+kovQNJRR+HIzQXTwpnfPfF62kUXETjhBMBKLIcFnqGHNLTpiisx6+rAMnHk2VUKPT2djGuvBeqXsRJVt/rtMuvq9ljNjpWXk3bB+Y0qmf0btnfqVFzx0N/49bR4INydI8euaWrJyYl5FLXhMjnugYNaXFZP75Z47DtsLIrT3mfeUaMSr6eccgqxstJmy7oHDEw8Tr/wgsSXSzXZPs/SDAYTP//ozp2sHj2GPu+9S87/3WZPD4dxDxpEt8svA0XF2aOh8hI44Se4Bw9OVLXjJ0fiHthQ0Um/+GI72CkKrkK7u7bq95P9m9/Yox6ramI5FCURKJ0FBeTecw+oCqrH0/Cex0/DNXBA/LxLFXsloKWkNLznzy8heeYpKKqKI79H4vXuf3kMDCOxXP02N/kdKClh9egx9P3g/YZ9EArR4+9/B9PAMkywTCzDQNEbfXaPOQZnj55gGji6N3x20y+4gOjxx4Nh2subFpgGnhEjm/xcjJoaMEwc2fY1e7WUFFLPPRdME8s0wIjfm1bi4JgjK4ukaVPt5Rq9p6t3H3zjx9s/60bLu3oXJOZx5nfHKO2HpSo4k3ytHmipiB9oqdtuv6cVDmNWVdn7pdHPJbptG3Xz57M714ABZFxuh8zqjz6i/PkXAPt32jvCPvix41e32T0CdpN9x+2knnkmlmWxavAQFIcDxeWi4NVXcHbvTnDpUnb85jeoTheKy4XidtmPPW7y7r4bgOCSJVR/8gmqy4WzoDeBqccBdu+QWGmZHYrdbhSnC8XlRM/IwNEtI3HAMbp+HVYshqN7PprfhxkKEVy2DAwDKxbDisXijw38kyehejxEd+yg5vPPwTBQ/X6STzwRsEN23ZIlEDOwDAOMGFY0hrNPb1JPPx2Asn/+0+4dEDNInjEd/8SJAGy59DL7IGT9srEYlmGQ9atb8Y4YQbR4J5vOPTfxet+P56CoKhWvvU7Rb39rvx6LJf6OOXr0oO8H7wNQ+tfHST3rLBxZSa1WcolGwNW067oQQogDxwFxCZMXX3yR8847j8cff5yxY8fywAMP8PLLL7N69WoyM/d+zld7DYFuhsOoLlfi/mC1esyh9F+w58FyDlSmaaFgNalmH2xWDR/BgCWLO3szOtXBtg8Sf/taGVnUDIdRdB1F0zAjEaLbttm9JqIxPIfY3SjDGzYQ+vZb+5SBiH3wygpH7LB8hh2gKl57nbov52GGIyQdOYXkk+yDV1t+finR7dvs3hz1pxuEw2Tf/mtSpk/HikRYNXRYYnv7fvoJjqwsaj79lC0/v7RZexS3O/HzK3vmGYr/eCcA/ilTyP/LY4n3rPn0U3uB+tMG4geBYqWlrD3mWPq883Yi9Bs1NWh+P5EtW1h3zLEt7se+c2bjyM2l5vO5bIl3l3b26kWf994FoPiuuyl76qlmy/knTyb/r4/b23X5FdTMmQNA1q23kHbeeYD9mbRCoWbL5v/1cfyTJxMtLmbt5CMSrw9YvgzF4aDi1dfYceutzZZz5ObSd47dm2Dngw+Rec3ViR4tqZc39Ggpf+zBRI+WtiCXMBFCiK7pgAiZY8eOZcyYMTzyyCMAmKZJfn4+V111Fb/85S/3urz8k2pfq0ePabMvFPujNePGd3g1uys52H/+cHDvg654oMWyLIyysnjPizDOHvkouk6srIzQim+xwiHMcDh+TnwIyzRJO/tsAGrnf0X1hx9ihcO4+vcn7Rz79eJ77iG4eIkdao0YvV9/PdFl2jIMiEbB4UDRtESXaYBo8U42X3QRiqaBrqFoeiKA5953H46sTEKrVrHroYdRNA09M5PseEW86v0PqP3ii92W1XD27kPKjOn2PB9+SHTLVhRdwztmTOL0iMo33wRA0XX7vN74e7qHDEFPT8eKRAiuWJF43TVgAIqqYtTUYlRUoOha/H3t6YqmNelB0/jgaqy6Bs3nxaitQ0/yN5v+Y8j/byGE6Jr2+5AZiUTwer385z//YXr8nC2A888/n4qKCv773/82WyYcDhOuP4cQ+59Ufn6+/JNqBwd7NVfaf3C3H2QfwMF5oKVJyCot5bsjptDvk4/R4+fdHmyfh/bq0SIhUwghuiZ177N0bSUlJRiGQVZW00spZGVlUVRU1OIyd955J8nJyYlbfn5+i/OJHy8xENJB9GWqMWn/wd1+kH1ghsMUzvuiYXCwg0Tjn7eenm5XIRsN7HTQfR727+PZQgghvqf9PmT+ELfccguVlZWJ25YtWzp7k4QQ4oB0sIfseop+wIyz972Z4bA9qvhBdqBBCCEOZvv9f71u3bqhaRrFxcVNXi8uLiY7PsDC7lwuF66D/AuPEEKIjtE4ZB2MYVsONAghxMFnv69kOp1ORo0axexG18gzTZPZs2czbtz3u5i2EEII0dYkZAkhhDjY7PeVTIDrr7+e888/n9GjR3PooYfywAMPUFtby4UXXtjZmyaEEEIIIYQQB5UDImSeccYZ7Nq1i1//+tcUFRUxfPhw3nvvvWaDAQkhhBBCCCGEaF/7/SVM2oIMgS6EEELsf+T/txBCdE37/TmZQgghhBBCCCG6DgmZQgghhBBCCCHajIRMIYQQQgghhBBtRkKmEEIIIYQQQog2IyFTCCGEEEIIIUSbkZAphBBCCCGEEKLNSMgUQgghhBBCCNFm9M7egK6g/lKhVVVVnbwlQgghhNhX9f+35ZLfQgjRtUjIBKqrqwHIz8/v5C0RQgghxPdVXV1NcnJyZ2+GEEKIOMWSw3+Ypsn27dtJSkpCUZQ2W29VVRX5+fls2bKFQCDQZuvdnxzs+0Daf3C3H2QfHOztB9kH7dl+y7Korq4mNzcXVZUzgIQQoquQSiagqirdu3dvt/UHAoGD8otFYwf7PpD2H9ztB9kHB3v7QfZBe7VfKphCCNH1yGE/IYQQQgghhBBtRkKmEEIIIYQQQog2IyGzHblcLm6//XZcLldnb0qnOdj3gbT/4G4/yD442NsPsg8O9vYLIcTBSAb+EUIIIYQQQgjRZqSSKYQQQgghhBCizUjIFEIIIYQQQgjRZiRkCiGEEEIIIYRoMxIyhRBCCCGEEEK0GQmZe3HnnXcyZswYkpKSyMzMZPr06axevbrJPKFQiCuuuIL09HT8fj8zZ86kuLi4yTxXX301o0aNwuVyMXz48D2+59q1a0lKSiIlJaWNW/P9dVT7N27ciKIozW5ffvllezZvrzry529ZFvfeey+FhYW4XC7y8vL4wx/+0F5N22cdtQ/uuOOOFj8DPp+vPZu3Vx35GXj//fc57LDDSEpKIiMjg5kzZ7Jx48Z2atm+68h98NJLLzF8+HC8Xi89e/bknnvuaa9m7bO2aP/SpUuZNWsW+fn5eDweBg4cyIMPPtjsvT755BNGjhyJy+Wib9++PP300+3dvH3SUftgx44dnHXWWRQWFqKqKtdee21HNE8IIUQbk5C5F59++ilXXHEFX375JR9++CHRaJRjjz2W2traxDzXXXcdb775Ji+//DKffvop27dv55RTTmm2rosuuogzzjhjj+8XjUaZNWsWEydObPO2/BAd3f6PPvqIHTt2JG6jRo1q8zZ9Hx3Z/muuuYa///3v3HvvvaxatYo33niDQw89tF3a9X101D74xS9+0eRnv2PHDgYNGsRpp53Wbm3bFx3V/g0bNnDyySdz5JFHsmTJEt5//31KSkpaXE9H66h98O6773L22Wdz6aWX8s033/DYY49x//3388gjj7Rb2/ZFW7R/4cKFZGZm8uyzz7JixQp+9atfccsttzRp24YNG/jJT37ClClTWLJkCddeey0XX3wx77//foe2tyUdtQ/C4TAZGRncdtttDBs2rEPbKIQQog1Z4nvZuXOnBViffvqpZVmWVVFRYTkcDuvll19OzLNy5UoLsObNm9ds+dtvv90aNmxYq+u/6aabrHPOOcd66qmnrOTk5Lbe/B+tvdq/YcMGC7AWL17cXpveJtqr/d9++62l67q1atWqdtv2ttLevwP1lixZYgHWZ5991mbb3hbaq/0vv/yypeu6ZRhG4rU33njDUhTFikQibd+QH6G99sGsWbOsU089tclrDz30kNW9e3fLNM22bcSP8GPbX+/yyy+3pkyZknh+0003WYMHD24yzxlnnGEdd9xxbdyCH6+99kFjkydPtq655po23W4hhBAdQyqZ31NlZSUAaWlpgH1kNhqNcvTRRyfmGTBgAD169GDevHnfa91z5szh5Zdf5tFHH227DW5j7dl+gJNOOonMzEwmTJjAG2+80TYb3Ybaq/1vvvkmvXv35q233qKgoIBevXpx8cUXU1ZW1rYNaAPt/Rmo9/e//53CwsIuU9Wv117tHzVqFKqq8tRTT2EYBpWVlfzrX//i6KOPxuFwtG0jfqT22gfhcBi3293kNY/Hw9atW9m0aVMbbHnbaKv2V1ZWJtYBMG/evCbrADjuuON+1O9Re2mvfSCEEOLAICHzezBNk2uvvZbDDz+cIUOGAFBUVITT6Wx2/mRWVhZFRUX7vO7S0lIuuOACnn76aQKBQFtudptpz/b7/X7uu+8+Xn75Zd5++20mTJjA9OnTu1TQbM/2r1+/nk2bNvHyyy/zzDPP8PTTT7Nw4UJOPfXUtmzCj9ae+6CxUCjEc889x09/+tMfu8ltqj3bX1BQwAcffMCtt96Ky+UiJSWFrVu38tJLL7VlE3609twHxx13HK+++iqzZ8/GNE3WrFnDfffdB9jn6nUFbdX+L774ghdffJFLLrkk8VpRURFZWVnN1lFVVUUwGGzbhvwI7bkPhBBCHBj0zt6A/ckVV1zBN998w9y5c9t83T/72c8466yzmDRpUpuvu620Z/u7devG9ddfn3g+ZswYtm/fzj333MNJJ53U5u/3Q7Rn+03TJBwO88wzz1BYWAjAP/7xD0aNGsXq1avp379/m7/nD9Ge+6Cx1157jerqas4///x2fZ/vqz3bX1RUxM9+9jPOP/98Zs2aRXV1Nb/+9a859dRT+fDDD1EUpc3f84do77+D69at44QTTiAajRIIBLjmmmu44447UNWucUy0Ldr/zTffcPLJJ3P77bdz7LHHtuHWdQzZB0IIIfama/zX3g9ceeWVvPXWW3z88cd079498Xp2djaRSISKioom8xcXF5Odnb3P658zZw733nsvuq6j6zo//elPqaysRNd1nnzyybZqxg/W3u1vydixY1m7du2PWkdbae/25+TkoOt6ImACDBw4EIDNmzf/uI1vIx35Gfj73//OCSec0Kyq05nau/2PPvooycnJ3H333YwYMYJJkybx7LPPMnv2bObPn99WzfhR2nsfKIrCXXfdRU1NDZs2baKoqCgx+FXv3r3bpA0/Rlu0/9tvv+Woo47ikksu4bbbbmsyLTs7u9mIvMXFxQQCATweT9s25gdq730ghBDiwCAhcy8sy+LKK6/ktddeY86cORQUFDSZPmrUKBwOB7Nnz068tnr1ajZv3sy4ceP2+X3mzZvHkiVLErff/va3JCUlsWTJEmbMmNFm7fm+Oqr9LVmyZAk5OTk/ah0/Vke1//DDDycWi7Fu3brEa2vWrAGgZ8+eP7IVP05HfwY2bNjAxx9/3GW6ynZU++vq6ppV6zRNA+xKd2fq6M+Apmnk5eXhdDp54YUXGDduHBkZGT+6HT9UW7V/xYoVTJkyhfPPP7/FyxONGzeuyToAPvzwwx/9t7QtdNQ+EEIIcYDovDGH9g+XXXaZlZycbH3yySfWjh07Ere6urrEPJdeeqnVo0cPa86cOdbXX39tjRs3zho3blyT9Xz33XfW4sWLrZ///OdWYWGhtXjxYmvx4sVWOBxu8X27yuiyHdX+p59+2nr++eetlStXWitXrrT+8Ic/WKqqWk8++WSHtnd3HdV+wzCskSNHWpMmTbIWLVpkff3119bYsWOtY445pkPb25KO/h247bbbrNzcXCsWi3VI+/amo9o/e/ZsS1EU6ze/+Y21Zs0aa+HChdZxxx1n9ezZs8l7dYaO2ge7du2y/vKXv1grV660Fi9ebF199dWW2+225s+f36Ht3V1btH/58uVWRkaGdc455zRZx86dOxPzrF+/3vJ6vdaNN95orVy50nr00UctTdOs9957r0Pb25KO2geWZSU+F6NGjbLOOussa/HixdaKFSs6rK1CCCF+PAmZewG0eHvqqacS8wSDQevyyy+3UlNTLa/Xa82YMcPasWNHk/VMnjy5xfVs2LChxfftKiGzo9r/9NNPWwMHDrS8Xq8VCASsQw89tMlQ+J2lI3/+27Zts0455RTL7/dbWVlZ1gUXXGCVlpZ2UEtb15H7wDAMq3v37tatt97aQa3bu45s/wsvvGCNGDHC8vl8VkZGhnXSSSdZK1eu7KCWtq6j9sGuXbusww47zPL5fJbX67WOOuoo68svv+zAlrasLdp/++23t7iOnj17Nnmvjz/+2Bo+fLjldDqt3r17N3mPztSR+2Bf5hFCCNG1KZZlWftU8hRCCCGEEEIIIfZCzskUQgghhBBCCNFmJGQKIYQQQgghhGgzEjKFEEIIIYQQQrQZCZlCCCGEEEIIIdqMhEwhhBBCCCGEEG1GQqYQQgghhBBCiDYjIVMIIYQQQgghRJuRkCmEEEIIIYQQos1IyBRCCCGEEEII0WYkZAoh9guWZXH00Udz3HHHNZv22GOPkZKSwtatWzthy4QQQgghRGMSMoUQ+wVFUXjqqaeYP38+f/3rXxOvb9iwgZtuuomHH36Y7t27t+l7RqPRNl2fEEIIIcTBQEKmEGK/kZ+fz4MPPsgvfvELNmzYgGVZ/PSnP+XYY49lxIgRTJs2Db/fT1ZWFueeey4lJSWJZd977z0mTJhASkoK6enpnHDCCaxbty4xfePGjSiKwosvvsjkyZNxu90899xzndFMIYQQQoj9mmJZltXZGyGEEN/H9OnTqays5JRTTuF3v/sdK1asYPDgwVx88cWcd955BINBbr75ZmKxGHPmzAHglVdeQVEUhg4dSk1NDb/+9a/ZuHEjS5YsQVVVNm7cSEFBAb169eK+++5jxIgRuN1ucnJyOrm1QgghhBD7FwmZQoj9zs6dOxk8eDBlZWW88sorfPPNN3z++ee8//77iXm2bt1Kfn4+q1evprCwsNk6SkpKyMjIYPny5QwZMiQRMh944AGuueaajmyOEEIIIcQBRbrLCiH2O5mZmfz85z9n4MCBTJ8+naVLl/Lxxx/j9/sTtwEDBgAkusR+9913zJo1i969exMIBOjVqxcAmzdvbrLu0aNHd2hbhBBCCCEONHpnb4AQQvwQuq6j6/afsJqaGk488UTuuuuuZvPVd3c98cQT6dmzJ0888QS5ubmYpsmQIUOIRCJN5vf5fO2/8UIIIYQQBzAJmUKI/d7IkSN55ZVX6NWrVyJ4NlZaWsrq1at54oknmDhxIgBz587t6M0UQgghhDgoSHdZIcR+74orrqCsrIxZs2axYMEC1q1bx/vvv8+FF16IYRikpqaSnp7O3/72N9auXcucOXO4/vrrO3uzhRBCCCEOSBIyhRD7vdzcXP73v/9hGAbHHnsshxxyCNdeey0pKSmoqoqqqvz73/9m4cKFDBkyhOuuu4577rmnszdbCCGEEOKAJKPLCiGEEEIIIYRoM1LJFEIIIYQQQgjRZiRkCiGEEEIIIYRoMxIyhRBCCCGEEEK0GQmZQgghhBBCCCHajIRMIYQQQgghhBBtRkKmEEIIIYQQQog2IyFTCCGEEEIIIUSbkZAphBBCCCGEEKLNSMgUQgghhBBCCNFmJGQKIYQQQgghhGgzEjKFEEIIIYQQQrSZ/wflq/RZh2yWJgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lineplot(data=exploitation, x=\"Year\", y=\"Exploitation\", hue=\"Domain\", style=\"Domain\", markers=True, err_style=None)\n",
    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
    "plt.savefig(\"plots/exploitation-domain.png\", bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "55417e66-5f9c-46f6-9acc-55899f9a5c7f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Exploitation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014</td>\n",
       "      <td>5259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015</td>\n",
       "      <td>5223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016</td>\n",
       "      <td>5707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017</td>\n",
       "      <td>5890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018</td>\n",
       "      <td>6620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019</td>\n",
       "      <td>6712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2020</td>\n",
       "      <td>8444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2021</td>\n",
       "      <td>9295</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Exploitation\n",
       "0  2014          5259\n",
       "1  2015          5223\n",
       "2  2016          5707\n",
       "3  2017          5890\n",
       "4  2018          6620\n",
       "5  2019          6712\n",
       "6  2020          8444\n",
       "7  2021          9295"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exploitation_total = exploitation.groupby(\"Year\").sum().reset_index()\n",
    "exploitation_total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ed6ad478-c6ed-4be5-9a50-b0489d7356dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lineplot(data=exploitation_total, x=\"Year\", y=\"Exploitation\")\n",
    "plt.savefig(\"plots/exploitation-total.png\", bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e3826b17-9ff9-4639-966e-ca241494197c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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      "text/plain": [
       "                              Domain   \\\n",
       "0   Physical Sciences and Geosciences   \n",
       "1   Physical Sciences and Geosciences   \n",
       "2   Physical Sciences and Geosciences   \n",
       "3   Physical Sciences and Geosciences   \n",
       "4   Physical Sciences and Geosciences   \n",
       "..                                ...   \n",
       "77                            General   \n",
       "78                            General   \n",
       "79                            General   \n",
       "80                            General   \n",
       "81                            General   \n",
       "\n",
       "                                             Journal  H5-index  H5-median  \\\n",
       "0                          AAS: The Astronomy Journal       82      134.0   \n",
       "1                      AAS: The Astrophysical Journal      161      239.0   \n",
       "2   AAS: The Astrophysical Journal Supplement Seri...       75      153.0   \n",
       "3                             Astronomy and Computing       23       41.0   \n",
       "4             Communications in Computational Physics       27       41.0   \n",
       "..                                                ...      ...        ...   \n",
       "77      The Journal of Open Source Software [example]       48      114.0   \n",
       "78       Journal of Software: Practice and Experience       31       53.0   \n",
       "79                  Research Ideas and Outcomes (RIO)       18       26.0   \n",
       "80  SIAM Journal on Scientific Computing (SISC) So...       53       71.0   \n",
       "81                                          SoftwareX       27       40.0   \n",
       "\n",
       "   Simple H  \n",
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       "..      ...  \n",
       "77      NaN  \n",
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       "\n",
       "[82 rows x 5 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "h_index = pd.read_csv(\"data/SoftwareSurveyData - h5-index-compute.csv\")\n",
    "h_index"
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  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "25db83d7-4f0d-4479-b28a-449c73da2725",
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   "outputs": [
    {
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       "                                             Journal  H5-index  H5-median\n",
       "0                          AAS: The Astronomy Journal       82      134.0\n",
       "1                      AAS: The Astrophysical Journal      161      239.0\n",
       "2   AAS: The Astrophysical Journal Supplement Seri...       75      153.0\n",
       "3                             Astronomy and Computing       23       41.0\n",
       "4             Communications in Computational Physics       27       41.0\n",
       "..                                                ...      ...        ...\n",
       "77      The Journal of Open Source Software [example]       48      114.0\n",
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       "79                  Research Ideas and Outcomes (RIO)       18       26.0\n",
       "80  SIAM Journal on Scientific Computing (SISC) So...       53       71.0\n",
       "81                                          SoftwareX       27       40.0\n",
       "\n",
       "[71 rows x 3 columns]"
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     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "h_index = h_index.drop(columns=[\"Domain \", \"Simple H\"]).dropna()\n",
    "h_index"
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  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d8341008-72f4-419f-a536-7613cd543367",
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       "                               Domain  \\\n",
       "0   Physical Sciences and Geosciences   \n",
       "1   Physical Sciences and Geosciences   \n",
       "2   Physical Sciences and Geosciences   \n",
       "3   Physical Sciences and Geosciences   \n",
       "4   Physical Sciences and Geosciences   \n",
       "..                                ...   \n",
       "77                            General   \n",
       "78                            General   \n",
       "79                            General   \n",
       "80                            General   \n",
       "81                            General   \n",
       "\n",
       "                                              Journal  Archiving  \\\n",
       "0                          AAS: The Astronomy Journal          3   \n",
       "1                      AAS: The Astrophysical Journal          3   \n",
       "2   AAS: The Astrophysical Journal Supplement Seri...          3   \n",
       "3                             Astronomy and Computing          3   \n",
       "4             Communications in Computational Physics          1   \n",
       "..                                                ...        ...   \n",
       "77      The Journal of Open Source Software [example]          1   \n",
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       "79                  Research Ideas and Outcomes (RIO)          1   \n",
       "80  SIAM Journal on Scientific Computing (SISC) So...          1   \n",
       "81                                          SoftwareX          3   \n",
       "\n",
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       "\n",
       "    Depedencies  Documentation  Application  Future Development   H5-index  \\\n",
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       "..          ...            ...          ...                  ...       ...   \n",
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       "81         40  \n",
       "\n",
       "[70 rows x 14 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "h_index = reqs_raw.join(h_index.set_index(\"Journal \"), on=\"Journal\").dropna()\n",
    "h_index = h_index.drop(columns=[\"Instructions for paper preparation (link)\", \"Description\"])\n",
    "h_index[\"H5-index\"] = h_index[\"H5-index\"].astype(int)\n",
    "h_index[\"H5-median\"] = h_index[\"H5-median\"].astype(int)\n",
    "h_index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f0d58a20-8ffd-4c7d-8bb5-f20d588e00e5",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
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       "      <td>1</td>\n",
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      "text/plain": [
       "                               Domain  \\\n",
       "0   Physical Sciences and Geosciences   \n",
       "1   Physical Sciences and Geosciences   \n",
       "2   Physical Sciences and Geosciences   \n",
       "3   Physical Sciences and Geosciences   \n",
       "4   Physical Sciences and Geosciences   \n",
       "..                                ...   \n",
       "77                            General   \n",
       "78                            General   \n",
       "79                            General   \n",
       "80                            General   \n",
       "81                            General   \n",
       "\n",
       "                                              Journal  Archiving  \\\n",
       "0                          AAS: The Astronomy Journal          3   \n",
       "1                      AAS: The Astrophysical Journal          3   \n",
       "2   AAS: The Astrophysical Journal Supplement Seri...          3   \n",
       "3                             Astronomy and Computing          3   \n",
       "4             Communications in Computational Physics          1   \n",
       "..                                                ...        ...   \n",
       "77      The Journal of Open Source Software [example]          1   \n",
       "78       Journal of Software: Practice and Experience          1   \n",
       "79                  Research Ideas and Outcomes (RIO)          1   \n",
       "80  SIAM Journal on Scientific Computing (SISC) So...          1   \n",
       "81                                          SoftwareX          3   \n",
       "\n",
       "    Persistnt Link  License  Functionality  Project  Quality + Testing  \\\n",
       "0                3        3              1        1                  1   \n",
       "1                3        3              1        1                  1   \n",
       "2                3        3              1        1                  1   \n",
       "3                3        3              1        2                  1   \n",
       "4                1        1              1        1                  1   \n",
       "..             ...      ...            ...      ...                ...   \n",
       "77               1        3              1        1                  1   \n",
       "78               1        1              1        1                  1   \n",
       "79               1        1              1        1                  1   \n",
       "80               1        1              1        1                  1   \n",
       "81               3        3              1        1                  3   \n",
       "\n",
       "    Depedencies  Documentation  Application  Future Development   H5-index  \\\n",
       "0             3              3            1                    1        82   \n",
       "1             3              3            1                    1       161   \n",
       "2             3              3            1                    1        75   \n",
       "3             1              3            1                    1        23   \n",
       "4             1              0            0                    0        27   \n",
       "..          ...            ...          ...                  ...       ...   \n",
       "77            2              3            3                    2        48   \n",
       "78            1              1            1                    1        31   \n",
       "79            1              0            0                    0        18   \n",
       "80            1              0            0                    0        53   \n",
       "81            1              3            3                    1        27   \n",
       "\n",
       "    H5-median  Requirements  \n",
       "0         134             5  \n",
       "1         239             5  \n",
       "2         153             5  \n",
       "3          41             5  \n",
       "4          41             0  \n",
       "..        ...           ...  \n",
       "77        114             5  \n",
       "78         53             0  \n",
       "79         26             0  \n",
       "80         71             0  \n",
       "81         40             6  \n",
       "\n",
       "[70 rows x 15 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def count_reqs(row):\n",
    "    count = 0\n",
    "    for col in row.index:\n",
    "        if col not in [\n",
    "            \"Journal\",\n",
    "            \"H5-index\",\n",
    "            \"H5-median\",\n",
    "            \"Domain\",\n",
    "        ]:\n",
    "            if row[col] > 1:\n",
    "                count += 1\n",
    "    \n",
    "    return count\n",
    "\n",
    "h_index[\"Requirements\"] = h_index.apply(count_reqs, axis=1)\n",
    "h_index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "6d6c94ad-986e-4c98-9b0e-59ff4dcbfa63",
   "metadata": {},
   "outputs": [
    {
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       "      <td>General</td>\n",
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       "      <td>27</td>\n",
       "      <td>40</td>\n",
       "      <td>6</td>\n",
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       "</table>\n",
       "<p>70 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                               Domain  \\\n",
       "0   Physical Sciences and Geosciences   \n",
       "1   Physical Sciences and Geosciences   \n",
       "2   Physical Sciences and Geosciences   \n",
       "3   Physical Sciences and Geosciences   \n",
       "4   Physical Sciences and Geosciences   \n",
       "..                                ...   \n",
       "77                            General   \n",
       "78                            General   \n",
       "79                            General   \n",
       "80                            General   \n",
       "81                            General   \n",
       "\n",
       "                                              Journal  H5-index  H5-median  \\\n",
       "0                          AAS: The Astronomy Journal        82        134   \n",
       "1                      AAS: The Astrophysical Journal       161        239   \n",
       "2   AAS: The Astrophysical Journal Supplement Seri...        75        153   \n",
       "3                             Astronomy and Computing        23         41   \n",
       "4             Communications in Computational Physics        27         41   \n",
       "..                                                ...       ...        ...   \n",
       "77      The Journal of Open Source Software [example]        48        114   \n",
       "78       Journal of Software: Practice and Experience        31         53   \n",
       "79                  Research Ideas and Outcomes (RIO)        18         26   \n",
       "80  SIAM Journal on Scientific Computing (SISC) So...        53         71   \n",
       "81                                          SoftwareX        27         40   \n",
       "\n",
       "    Requirements  \n",
       "0              5  \n",
       "1              5  \n",
       "2              5  \n",
       "3              5  \n",
       "4              0  \n",
       "..           ...  \n",
       "77             5  \n",
       "78             0  \n",
       "79             0  \n",
       "80             0  \n",
       "81             6  \n",
       "\n",
       "[70 rows x 5 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "h_index = h_index[[\"Domain\", \"Journal\", \"H5-index\", \"H5-median\", \"Requirements\"]]\n",
    "h_index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "ad1ac2b9-73bf-49ef-a35a-09b580db0bc9",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(data=h_index, x=\"Requirements\", y=\"H5-index\")\n",
    "plt.savefig(\"plots/h5-index.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "602a9a66-b2bb-49e8-a9c0-802ed502cd4c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot(data=h_index, x=\"Requirements\", y=\"H5-index\", order=2)\n",
    "plt.savefig(\"plots/h5-index-reg.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "d1b02786-0d3f-47f9-88ad-39b797deb0b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(data=h_index, x=\"Requirements\", y=\"H5-index\")\n",
    "plt.savefig(\"plots/h5-index-box.png\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
